• 전자공학회논문지
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• 제51권1호
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• pp.195-201
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• 2014

본 연구에서는 $(2D)^2PCA$ 알고리즘을 이용한 pRBFNNs 패턴분류기 기반 얼굴인식 시스템을 설계하였다. 기존의 1차원 PCA는 행과 열의 곱으로 표현한 이미지의 차원을 축소한다. 하지만 $(2D)^2PCA$(2-Directional 2-Dimensional Principal Components Analysis)는 이미지의 행과 열에서 각각 차원축소를 수행한다. 그 다음 제안된 지능형 패턴분류기로 축소된 이미지를 사용하여 성능을 평가한다. (pRBFNNs)로 성능 평가를 한다. 제안된 다항식 기반 RBFNNs은 조건부, 결론부, 추론부 세가지의 기능적 모듈로 구성되어 있고 조건는 퍼지 클러스터링을 사용하여 입력 공간을 분할하고, 결론부는 RBFNNs의 연결가중치로 일차 선형식으로 표현한다. 또한 차분진화 알고리즘을 이용하여 제안된 분류기의 파라미터, 즉 입력의 수, 퍼지 클러스터링의 퍼지화 계수를 최적화 한다. 얼굴인식에 많이 사용되는 Yale과 AT&T를 사용하여 인식률을 평가하였다. 실험 평가를 위해 IC&CI 연구실 데이터를 추가하여 실험하였다.

• Parasites, Hosts and Diseases
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• 제59권6호
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• pp.547-556
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• 2021

Our objective was to investigate whether inflammatory microenvironment induced by Trichomonas vaginalis infection can stimulate proliferation of prostate cancer (PCa) cells in vitro and in vivo mouse experiments. The production of CXCL1 and CCL2 increased when cells of the mouse PCa cells (TRAMP-C2 cell line) were infected with live T. vaginalis. T. vaginalis-conditioned medium (TCM) prepared from co-culture of PCa cells and T. vaginalis increased PCa cells migration, proliferation and invasion. The cytokine receptors (CXCR2, CCR2, gp130) were expressed higher on the PCa cells treated with TCM. Pretreatment of PCa cells with antibodies to these cytokine receptors significantly reduced the proliferation, mobility and invasiveness of PCa cells, indicating that TCM has its effect through cytokine-cytokine receptor signaling. In C57BL/6 mice, the prostates injected with T. vaginalis mixed PCa cells were larger than those injected with PCa cells alone after 4 weeks. Expression of epithelial-mesenchymal transition markers and cyclin D1 in the prostate tissue injected with T. vaginalis mixed PCa cells increased than those of PCa cells alone. Collectively, it was suggested that inflammatory reactions by T. vaginalis-stimulated PCa cells increase the proliferation and invasion of PCa cells through cytokine-cytokine receptor signaling pathways.

• KSBB Journal
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• 제21권1호
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• pp.59-67
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• 2006

본 연구에서는 2차원 형광스펙트럼의 PCA 분석을 통하여 발효 공정을 모니터링하고 PCR과 PLS과 같은 다변량 분석기법을 이용하여 공정을 모델링하였다. 재조합 대장균 E. coli 와 효모 S.cerevisiae의 발효 공정 중에 얻어진 많은 양의 2차원 형광스펙트럼 자료는 우선 PCA를 통해 축소된다. 그리고 PCA에서 주성분점수와 적재 산점도는 발효 공정의 정성적 경향을 묘사하기 위해 사용되었다. 또한, PCR과 PLS는 2차원 형광스펙트럼의 분석을 위해 사용되었으며 PLS모델이 보정과 예측 능력에서 PCR모델보다 조금 더 우수한 성능을 나타냈다. 따라서 2차원 형광스펙트럼 자료를 이용하여 생물공정을 모델링 하고자 할 때는 PCR 방법보다는 PLS 방법을 사용하는 것이 유리할 것이다.

• 한국정보과학회논문지:소프트웨어및응용
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• 제29권8호
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• pp.521-528
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• 2002

본 논문에서는 문자인식의 특징선택방법으로 2차원 웨이브렛 패킷을 이용하는 새로운 방법을 제안한다. 영상자료의 특징들로부터 중심특징을 선택하기 위한 차원축소 기법으로 주성분분석 기법이 주로 사용된다. 하지만, 주성분분석 기법은 고유시스템에 의존하기 때문에, 이상치나 잡음 등에 민감할 뿐만 아니라, 전역적 특징만을 선택하는 경향이 있다. 때때로, 영상자료의 중요한 특징이 가장자리 부분이나 뽀족한 부분 같은 지역적 정보일 수 있다. 이러한 경우, 주성분분석 기법은 좋은 결과를 줄 수 없다. 또한 고유시스템은 많은 계산시간을 요구한다. 본 논문에서 원 자료는 2차원 웨이브렛 패킷기저에 의해 변환되고, 최적 판별 기저가 탐색된 후, 그것으로부터 적절한 특징이 선택된다. 주성분분석 기법과 비교하여, 제안된 방법은 웨이브렛의 좋은 특성에 의해 전역적 특징뿐만 아니라 지역적 특징의 선택이 빠른 계산시간으로 이루어진다. 제안된 방법의 성능을 보이기 위해 PCA와 제안된 방법의 인식률의 실험결과가 분석되었다.

• 한국산학기술학회논문지
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• 제15권9호
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• pp.5446-5451
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• 2014

내비게이션 단말기에 사용되는 전자지도 제작이 수작업으로 이루어지고 있어 오기가 발생할 수 있기 때문에, 본 논문에서는 내비게이션 정보의 요소로 다루어지는 교통 표지판에 대한 오프라인 자동 인식에 대해 제안하였다. 컴퓨터 비전과 패턴 인식 응용 분야로 2차원 얼굴 인식 분야에 널리 활용되고 있는 주성분분석기법(PCA)과 선형판별분석기법(LDA)을 이용하여 교통표지판을 인식하고자 한다. 먼저 PCA를 이용하여 높은 차원의 2차원 이미지 데이터를 저차원의 특징 벡터영역으로 투영을 시킨다. PCA로부터 구해진 저차원의 특징 벡터를 이용하여 LDA로 분산 매트릭스들 간에 최대가 되고 하고, 분산 매트릭스 내에서는 최소가 되도록 하였다. 실제 도로 환경에서 추출된 교통 신호판의 대부분을 제안된 알고리즘에 의해서 특징 벡터를 40개 이상 사용하였을 경우 92.3%이상의 높은 인식률을 보임을 확인하였다.

• 한국산업보건학회지
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• 제34권3호
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• pp.279-291
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• 2024

Objective: This was to develop headforms for the labor population, based on a three-dimensional(3D) face dimensions data base(DB) and a principal component analysis(PCA) fit test panel, in selection, use and maintenance of respirators in Korea. Methods: This study was part of a two-year-project initiated in 2021. The study was designed and conducted in line with ISO 16976-2 while subjects were those employed in the development of the PCA fit test panel. The approaches included literature review; examination on conformity of the 3D face dimensions DB; and development of headforms representing the labor population. The mean data were used in order to construct each model of the headforms through a way of 3D modeling and 3D printing technology. Results: A total of 2,752 subjects were determined. Five models of headforms(small, medium, large, long-narrow, short-wide) were completely constructed for the labor population. For example, means of the 10 face dimensions for medium headform model were: minimum frontal breadth 106 mm, face width 136 mm, jaw width 127 mm, face length 111 mm, interpupillary distance 69 mm, head breadth 164 mm, nose protrusion 12 mm, nose breadth 34 mm, nasal root breadth 35 mm, and nose length 50 mm. Conclusions: Five models of headforms were newly constructed using the study data. It is likely desirable that the constructed headforms, together with the 3D face dimensions DB as well as the PCA fit test panel, can be utilized more effectively in selection, use and maintenance of respirators for users including the labor population.

• Asian Pacific Journal of Cancer Prevention
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• 제14권10호
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• pp.5663-5669
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• 2013

The histone methyltransferase EZH2 (enhancer of zeste homolog 2) plays critical roles in prostate cancer (PCa) development and is a potential target for PCa treatment. Triptolide possesses anti-tumor activity, but it is unknown whether its therapeutic effect relates with EZH2 in PCa. Here we described EZH2 as a target for Triptolide in PCa cells. Our data showed that Triptolide suppressed PCa cell growth and reduced the expression of EZH2. Overexpression of EZH2 attenuated the Triptolide induced cell growth inhibition. Moreover, Triptolide treatment of PC-3 cells resulted in elevated mRNA levels of target genes (ADRB2, CDH1, CDKN2A and DAB2IP) negatively regulated by EZH2 as well as reduced mRNA levelsan of EZH2 positively regulated gene (cyclin D1). Our findings suggest the PCa cell growth inhibition mediated by Triptolide might be associated with downregulation of EZH2 expression and the subsequent modulation of target genes.

• 디지털산업정보학회논문지
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• 제9권2호
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• pp.111-119
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• 2013

Face recognition has recently become one of the most popular research areas in the fields of computer vision, machine learning, and pattern recognition because it spans numerous applications, such as access control, surveillance, security, credit-card verification, and criminal identification. In this paper, we propose a simple descriptor called an ECSP(Extended Center-Symmetric Pattern) for illumination-robust face recognition. The ECSP operator encodes the texture information of a local face region by emphasizing diagonal components of a previous CS-LBP(Center-Symmetric Local Binary Pattern). Here, the diagonal components are emphasized because facial textures along the diagonal direction contain much more information than those of other directions. The facial texture information of the ECSP operator is then used as the input image of an image covariance-based feature extraction algorithm such as 2D-PCA(Two-Dimensional Principal Component Analysis). Performance evaluation of the proposed approach was carried out using various binary pattern operators and recognition algorithms on the Yale B database. The experimental results demonstrated that the proposed approach achieved better recognition accuracy than other approaches, and we confirmed that the proposed approach is effective against illumination variation.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2005년도 추계종합학술대회
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• pp.1157-1160
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• 2005

The denoising and reconstruction of color images are increasingly studied in the field of computer vision and image processing. Especially, the denoising and reconstruction of color face images are more difficult than those of natural images because of the structural characteristics of human faces as well as the subtleties of color interactions. In this paper, we propose a denoising method based on PCA reconstruction for removing complex color noises on human faces, which is not easy to remove by using vectorial color filters. The proposed method is composed of the following five steps; training of canonical eigenface space using PCA, automatic extracting of face features using active appearance model, relighing of reconstructed color image using bilateral filter, extraction of noise regions using the variance of training data, and reconstruction using partial information of input images (except the noise regions) and blending of the reconstructed image with the original image. Experimental results show that the proposed denosing method efficiently removes complex color noises on input face images.

• Asian Pacific Journal of Cancer Prevention
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• 제16권2호
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• pp.595-600
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• 2015

Background: Accumulating evidence suggests that metformin possesses anticarcinogenic properties, and its use is associated with favorable outcomes in several cancers. However, it remains unclear whether metformin influences prognosis in prostate cancer (PCa) with concurrent type 2 diabetes (T2D). Materials and Methods: We searched PubMed, EMBASE, and the Cochrane Library from database inception to April 16, 2014 without language restrictions to identify studies investigating the effect of metformin treatment on outcomes of PCa with concurrent T2D. We conducted a meta-analysis to quantify the risk of recurrence, progression, cancer-specific mortality, and all-cause mortality. Summary relative risks (RRs) with corresponding 95% confidence intervals (CIs) were calculated. Publication bias was assessed by Begg's rank correlation test. Results: A total of eight studies fulfilled the eligibility criteria. We found that diabetic PCa patients who did not use metformin were at increased risk of cancer recurrence (RR, 1.20; 95%CI, 1.00-1.44), compared with those who used metformin. A similar trend was observed for other outcomes, but their relationships did not reach statistical significance. Funnel plot asymmetry was not observed among studies reporting recurrence (p=0.086). Conclusions: Our results suggest that metformin may improve outcomes in PCa patients with concurrent T2D. Well-designed large studies and collaborative basic research are warranted.