• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.1
• /
• pp.195-201
• /
• 2014

In this study, face recognition system was designed based on polynomial Radial Basis Function Neural Networks(pRBFNNs) pattern classifier using 2-directional 2-dimensional principal component analysis algorithm. Existing one dimensional PCA leads to the reduction of dimension of image expressed by the multiplication of rows and columns. However $(2D)^2PCA$(2-Directional 2-Dimensional Principal Components Analysis) is conducted to reduce dimension to each row and column of image. and then the proposed intelligent pattern classifier evaluates performance using reduced images. The proposed pRBFNNs consist of three functional modules such as the condition part, the conclusion part, and the inference part. In the condition part of fuzzy rules, input space is partitioned with the aid of fuzzy c-means clustering. In the conclusion part of rules. the connection weight of RBFNNs is represented as the linear type of polynomial. The essential design parameters (including the number of inputs and fuzzification coefficient) of the networks are optimized by means of Differential Evolution. Using Yale and AT&T dataset widely used in face recognition, the recognition rate is obtained and evaluated. Additionally IC&CI Lab dataset is experimented with for performance evaluation.

• Parasites, Hosts and Diseases
• /
• v.59 no.6
• /
• pp.547-556
• /
• 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
• /
• v.21 no.1 s.96
• /
• pp.59-67
• /
• 2006

2D spectrofluorometer produces many spectral data during fermentation processes. The fluorescence spectra are analyzed using chemometric methods such as principal component analysis (PCA), principal component regression (PCR) and partial least square regression (PLS). Analysis of the spectral data by PCA results in scores and loadings that are visualized in score-loading plots and used to monitor a few fermentation processes by S. cerevisae and recombinant E. coli. Two chemometric models were established to analyze the correlation between fluorescence spectra and process variables using PCR and PLS, and PLS was found to show slightly better calibration and prediction performance than PCR.

• Journal of KIISE:Software and Applications
• /
• v.29 no.8
• /
• pp.521-528
• /
• 2002

We propose a new approach to the feature selection for the classification of handwritten characters using two-dimensional(2D) wavelet packet bases. To extract key features of an image data, for the dimension reduction Principal Component Analysis(PCA) has been most frequently used. However PCA relies on the eigenvalue system, it is not only sensitive to outliers and perturbations, but has a tendency to select only global features. Since the important features for the image data are often characterized by local information such as edges and spikes, PCA does not provide good solutions to such problems. Also solving an eigenvalue system usually requires high cost in its computation. In this paper, the original data is transformed with 2D wavelet packet bases and the best discriminant basis is searched, from which relevant features are selected. In contrast to PCA solutions, the fast selection of detailed features as well as global features is possible by virtue of the good properties of wavelets. Experiment results on the recognition rates of PCA and our approach are compared to show the performance of the proposed method.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.15 no.9
• /
• pp.5446-5451
• /
• 2014

Because there are some mistakes by hand in processing electronic maps using a navigation terminal, this paper proposes an automatic offline recognition for traffic signs, which are considered ingredient navigation information. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), which have been used widely in the field of 2D face recognition as computer vision and pattern recognition applications, was used to recognize traffic signs. First, using PCA, a high-dimensional 2D image data was projected to a low-dimensional feature vector. The LDA maximized the between scatter matrix and minimized the within scatter matrix using the low-dimensional feature vector obtained from PCA. The extracted traffic signs under a real-world road environment were recognized successfully with a 92.3% recognition rate using the 40 feature vectors created by the proposed algorithm.

• Asian Pacific Journal of Cancer Prevention
• /
• v.14 no.10
• /
• pp.5663-5669
• /
• 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.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.9 no.2
• /
• pp.111-119
• /
• 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.

• Proceedings of the IEEK Conference
• /
• 2005.11a
• /
• pp.1157-1160
• /
• 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
• /
• v.16 no.2
• /
• pp.595-600
• /
• 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.

• The Korean Journal of Pain
• /
• v.12 no.2
• /
• pp.200-204
• /
• 1999

Background: Patient-controlled analgesia (PCA) has proven to be safe and effective in children from age 5 years, and older and compares favourably with continuous morphine infusion in the older child. We compared fentanyl and butorphanol for opioid use in PCA with ketorolac to determine a suitable drug combination for post-tonsillectomy pain control. Methods: We studied 60 patients, aged 5~12 yrs, undergoing tonsillectomy with or without adenoidectomy under general anesthesia using $N_2O-O_2$-enflurane. Patients were randomly assigned to receive fentanyl $250\;{\mu}g$ (Group 1: n=30) or butorphanol 5 mg (Group 2: n=30) mixed with ketorolac 90 mg and ondansetron 4 mg diluting 100 ml of 5% D/W solutions intravenously via PCA pump after operation. PCA pump were programmed to deliver a 0.05 ml/kg loading dose, 0.01 ml/kg/hr basal infusion, 0.01 ml/kg on demand bolus, 6 min lockout intervals between doses and 4 bolus hourly limit. Total infusion dosage of PCA drug, VAS pain scores, side effects and satisfaction score of both groups were monitored for 48 hrs. Results: Total infusion dosages were fentanyl $170.6\;{\mu}g$ with ketorolac 61.4 mg (Group 1) and butorphanol 2.8 mg with ketorolac 50.4 mg (Group 2). Total infusion dosage, quality of analgesia, side effects and overall satisfaction didn't differ between two groups. Conclusions: Both fentanyl and butorphanol mixed with ketorolac were effective for post-tonsillectomy pain control using PCA pump in children as young as 5 years old.