• Asian Pacific Journal of Cancer Prevention
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• 제16권6호
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• pp.2561-2567
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• 2015

Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer death worldwide. Our study aimed to reveal molecular mechanisms. Microarray data of GSE15471 (including 39 matching pairs of pancreatic tumor tissues and patient-matched normal tissues) was downloaded from Gene Expression Omnibus (GEO) database. We identified differentially expressed genes (DEGs) in PDAC tissues compared with normal tissues by limma package in R language. Then GO and KEGG pathway enrichment analyses were conducted with online DAVID. In addition, principal component analysis was performed and a protein-protein interaction network was constructed to study relationships between the DEGs through database STRING. A total of 532 DEGs were identified in the 38 PDAC tissues compared with 33 normal tissues. The results of principal component analysis of the top 20 DEGs could differentiate the PDAC tissues from normal tissues directly. In the PPI network, 8 of the 20 DEGs were all key genes of the collagen family. Additionally, FN1 (fibronectin 1) was also a hub node in the network. The genes of the collagen family as well as FN1 were significantly enriched in complement and coagulation cascades, ECM-receptor interaction and focal adhesion pathways. Our results suggest that genes of collagen family and FN1 may play an important role in PDAC progression. Meanwhile, these DEGs and enriched pathways, such as complement and coagulation cascades, ECM-receptor interaction and focal adhesion may be important molecular mechanisms involved in the development and progression of PDAC.

• Communications for Statistical Applications and Methods
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• 제11권1호
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• pp.49-58
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• 2004

In this talk we proposed an asymptotic test for dimensionality in the latent variable model for probabilistic principal component analysis with missing values at random. Proposed algorithm is a sequential likelihood ratio test for an appropriate Normal latent variable model for the principal component analysis. Modified EM-algorithm is used to find MLE for the model parameters. Results from simulations and real data sets give us promising evidences that the proposed method is useful in finding necessary number of components in the principal component analysis with missing values at random.

• 한국안전학회지
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• 제29권6호
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• pp.34-39
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• 2014

This paper is aimed to prevent danger of electrical fire at cattle barn to detect resistive and capacitive leakage current component for wiring type and length. In order to analysis for electric leakage component for cattle barn sizes and normal buildings, this paper was studied field state investigation which are at cattle barn companies(10 companies) in Cheong-won location and normal buildings at Nam-bu market in Jeon-ju location. Market to deduce the problems of electric leakage component is analyzed. The resistive and capacitive leakage current component for wiring type and length is analyzed at Beon-young cattle barn. Results show that electric leakage component suggested in this paper are valuable and usable to electrical fire in leakage current based on environment factor, which will prevent severe damage to human beings and properties and reduce the electrical fires in cattle barn. It is acceptable for electrical equipment use in an cattle barn.

• 대한수학회보
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• 제55권6호
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• pp.1891-1908
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• 2018

In this paper, we investigate the existence of an S-shaped connected component in the set of positive solutions of the Dirichlet problem of the one-dimension Minkowski-curvature equation $$\{\(\frac{u^{\prime}}{\sqrt{1-u^{{\prime}2}}}\)^{\prime}+{\lambda}a(x)f(u)=0,\;x{\in}(0,1),\\u(0)=u(1)=0$$, where ${\lambda}$ is a positive parameter, $f{\in}C[0,{\infty})$, $a{\in}C[0,1]$. The proofs of main results are based upon the bifurcation techniques.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제55권5호
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• pp.265-270
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• 2006

In this paper EMI problems with induction motor drive system using multi-level inverters are investigated. The high power multi-level inverter usually operates with low switching frequency and produces large noises. Generally, EMI consists of the conduction component through source lines and emission component emitted to the space. This conduction component can be classified to the common-mode between source line and ground, and the normal-mode between lines. The EMI filters for the induction motor drive system are designed and implemented to reduce EMI noise. Finally the designed system is verified by the experiment. The experimental results show that both the normal mode and common mode noises are greatly reduced compared to the system without filters.

• 한국안전학회지
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• 제29권4호
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• pp.73-77
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• 2014

In the field of fault diagnosis, the deviations from normal operating conditions are monitored to identify the type of faults and find their root causes. One of the most representative methods is the statistical approaches, due to a large amount of advantages. However, ambiguous diagnosis results can be generated according to fault magnitudes, even if the same fault occurs. To tackle this issue, this work proposes principal component analysis (PCA) based method with qualitative information. The PCA model is constructed under normal operation data and the residuals from faulty conditions are calculated. The significant changes of these residuals are recorded to make the information for identifying the types of fault. This model can be employed easily and the tasks for building are smaller than these of other common approaches. The efficacy of the proposed model is illustrated in Tennessee Eastman process.

• 한국식품영양과학회지
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• 제27권5호
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• pp.920-927
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• 1998

The purpose of this study was to investigate the correlation between serum component and immune function in Korean female college students according to the body mass index. There were significant increased in weight, body fat, LBM, TBW, WHR in subjects as their BMI increase(p<0.001). It was found obese group had higher levels of serum components such as total cholesterol, LDL-cholesterol and Cu levels than those of the normal group. There was a significant positive correlation between HDL-cholesterol level and NK cell number(p<0.01), between A/G ratio and T lympocytes number(p<0.05), between Cu levels and B lympocytes(p<0.01) in normal group. There was a significant positive correlation between TG level and CD4/8 ratio(p<0.001), between and IgG(p<0.001) in obese group.

• Tribology and Lubricants
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• 제22권3호
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• pp.119-126
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• 2006

In this paper, the contact behavior characteristics of a primary sealing components such as a seal ring and a seal seat has been presented for a small hydro-power turbine. Using the non-linear FEM analysis, the maximum temperature, the axial displacement, radial differences between a seal ring and a seal seat, and maximum contact normal stress have been analyzed for three optimized sealing profiles in which are designed based on the FEM analysis and Taguchi's experimental method. The three primary sealing profiles between a seal ring and a seal seat are strongly related to a leakage of a water for a hydro-power turbine and wear of a primary sealing component. The computed results show that the contact rubbing area between a seal ring and a seal seat is very important for reducing a friction heating and wear in a sealing gap, and increasing a contact normal stress in primary sealing components. Based on the FEM computation, models II and III in which have a small rubbing surface of seal rings show low dilatation of primary sealing components, and high normal contact stress between a seal ring and a seal seat. Thus, the FEM computed results recommend a short contacting width of a primary sealing component for reducing a leakage and thermal distortions, and expanding a seal life. This means that a conventional primary sealing component may be switched to a reduced sealing face of seal rings.

• 대한물리의학회지
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• 제4권4호
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• pp.249-255
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• 2009

Purpose：To investigate of gait component in Parkinson's Disease patient. Methods：participated Parkinson's Disease patient(n=12) and Normal adult(n=13). gait measure used by GaitRite. Results：SPSS for win version 12 was used for statistic analysis and independent t-test used to find between two groups. In the comparison of temporal parameter of gait between groups, the swing phase was significant decreased in Parkinson's groups, in the stance phase was significant increased in Normal groups, in the single support was significant decreased in Parkinson's groups and in the double support was significant increased in Parkinson's groups(p<.05). In the asymmetrical ratio of singele support was significant increased in Parkinson's groups(p<.05), and the swing phase and stance phase was significant increased in Parkinson's groups(p<.05). Conclusion：In the Parkinson's Disease patient gait showed temporal and spatial component variable changes comparison normal adult. therefore, it was seems to very important considerable at gait tranning in clinical intervention.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2008년도 학술발표회 논문집
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• pp.694-698
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• 2008

In hydrology, it is a difficult task to deal with multivariate time series such as modeling streamflows of an entire complex river system. Normal distribution based model such as MARMA (Multivariate Autorgressive Moving average) has been a major approach for modeling the multivariate time series. There are some limitations for the normal based models. One of them might be the unfavorable data-transformation forcing that the data follow the normal distribution. Furthermore, the high dimension multivariate model requires the very large parameter matrix. As an alternative, one might be decomposing the multivariate data into independent components and modeling it individually. In 1985, Lins used Principal Component Analysis (PCA). The five scores, the decomposed data from the original data, were taken and were formulated individually. The one of the five scores were modeled with AR-2 while the others are modeled with AR-1 model. From the time series analysis using the scores of the five components, he noted "principal component time series might provide a relatively simple and meaningful alternative to conventional large MARMA models". This study is inspired from the researcher's quote to develop a multivariate simulation model. The multivariate simulation model is suggested here using Principal Component Analysis (PCA) and Independent Component Analysis (ICA). Three modeling step is applied for simulation. (1) PCA is used to decompose the correlated multivariate data into the uncorrelated data while ICA decomposes the data into independent components. Here, the autocorrelation structure of the decomposed data is still dominant, which is inherited from the data of the original domain. (2) Each component is resampled by block bootstrapping or K-nearest neighbor. (3) The resampled components bring back to original domain. From using the suggested approach one might expect that a) the simulated data are different with the historical data, b) no data transformation is required (in case of ICA), c) a complex system can be decomposed into independent component and modeled individually. The model with PCA and ICA are compared with the various statistics such as the basic statistics (mean, standard deviation, skewness, autocorrelation), and reservoir-related statistics, kernel density estimate.