• Asian Pacific Journal of Cancer Prevention
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• 제13권5호
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• pp.1911-1915
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• 2012

Aim: New technologies for the early detection of pancreatic cancer (PC) are urgently needed. The aim of the present study was to screen for the potential protein biomarkers in serum using proteomic fingerprint technology. Methods: Magnetic beads combined with surface-enhanced laser desorption/ionization (SELDI) TOF MS were used to profile and compare the protein spectra of serum samples from 85 patients with pancreatic cancer, 50 patients with acute-on-chronic pancreatitis and 98 healthy blood donors. Proteomic patterns associated with pancreatic cancer were identified with Biomarker Patterns Software. Results: A total of 37 differential m/z peaks were identified that were related to PC (P < 0.01). A tree model of biomarkers was constructed with the software based on the three biomarkers (7762 Da, 8560 Da, 11654 Da), this showing excellent separation between pancreatic cancer and non-cancer., with a sensitivity of 93.3% and a specificity of 95.6%. Blind test data showed a sensitivity of 88% and a specificity of 91.4%. Conclusions: The results suggested that serum biomarkers for pancreatic cancer can be detected using SELDI-TOF-MS combined with magnetic beads. Application of combined biomarkers may provide a powerful and reliable diagnostic method for pancreatic cancer with a high sensitivity and specificity.

• Structural Engineering and Mechanics
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• 제42권6호
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• pp.867-882
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• 2012

Analytical (Rayleigh-Ritz method) and numerical studies are carried out and buckling interaction curves are developed for simply supported plates of varying aspect ratios ranging from 1 to 5, under the combined action of in-plane shear and tension. A multi-step buckling procedure is employed in the Finite Element (FE) model instead of a regular single step analysis in view of obtaining the buckling load under the combined forces. Both the analytical (classical) and FE studies confirm the delayed shear buckling characteristics of thin plate under the combined action of shear and tension. The interaction curves are found to be linear and are found to vary with plate aspect ratio. The interaction curve developed using Rayleigh-Ritz method is found to deviate in an increasing trend from that of validated FE model as plate aspect ratio is increased beyond value of 1. It is found that the observed deviation is due to the insufficient number of terms that is been considered in the assumed deflection function of Rayleigh-Ritz method and a convergence study is suggested as a solution.

• Geomechanics and Engineering
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• 제28권3호
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• pp.209-224
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• 2022

In this study, the numerical analysis model of π-beam explosion is established to compare and analyze the failure modes of the π-beam under the action of explosive loads, thus verifying the accuracy of the numerical model. Then, based on the numerical analysis of different protection forms of π beams under explosive loads, the peak pressure of π beam under different protection conditions, the law of structural energy consumption, the damage pattern of the π beam after protection, and the protection efficiency of different protective layers was studied. The testing results indicate that the pressure peak of π beam is relatively small under the combined protection of steel plate and aluminum foam, and the peak value of pressure decays quickly along the beam longitudinal. Besides, as the longitudinal distance increases, the pressure peak attenuates most heavily on the roof's explosion-facing surface. Meanwhile, the combined protective layer has a strong energy consumption capacity, the energy consumed accounts for 90% of the three parts of the π beam (concrete, steel, and protective layer). The damaged area of π beam is relatively small under the combined protection of steel plate and aluminum foam. We also calculate the protection efficiency of π beams under different protection conditions using the maximum spalling area of concrete. The results show that the protective efficiency of the combined protective layer is 45%, demonstrating a relatively good protective ability.

• 한국해안·해양공학회논문집
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• 제21권1호
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• pp.79-90
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• 2009

본 논문에서는 심해부터 천해에 까지 적용가능한 동적결합형 태풍 해일-조석-파랑 수치모델을 태풍 매미에 적용하여 모델의 안정성과 정확성을 검증하였다. 동적결합형 모델은 해수유동 모델인 POM을 수정한 모듈과 심해 풍파모델인 WAM을 심해부터 천해까지 적용가능하도록 수정한 모듈로 구성되어 있다. 수정 POM 모듈에서 조위, 조류 와 해일을 계산하며, 수정 WAM 모듈에서 풍파를 계산하여 상호 계산된 결과를 주고 받도록 결합된 동적결합형 모델이다. 수정 WAM 모듈에서는 잉여응력과 바람에 의한 마찰응력, 해수면 조도계수 등의 계산결과가 POM으로 제공되며 수정 POM 모듈에서는 유속, 조위면 등의 정보가 WAM으로 제공된다. 개발된 수치모델을 태풍 매미에 적용하여 계산된 결과를 관측된 파랑 및 조위자료와 비교하여 정확성을 검증하였다.

• 한국수자원학회논문집
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• 제45권5호
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• pp.455-464
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• 2012

이 논문에서는 관망시스템의 수격압 현상을 모의하기 위해서 합성 부정류 마찰 모형을 개발하였다. 부정류 마찰항을 고려하기 위한 방법으로 빈도 의존 마찰항과 순간 가속도 기반 마찰 모형을 합성하였으며, 특성선 방법을 모형 개발의 기반으로하였다. 관망에서의 부정류 모형으로 가장 널리 쓰이는 Zielke의 마찰항 모형과 Ramos의 마찰항 모형들과 종합적인 비교를 수행하였다. 모의 결과를 검증하기 위해서 고빈도로 수압을 측정할 수 있는 자료 획득체제를 구비한 관망시스템을 구축하였다. 정상상태에서 밸브 급폐로 야기된 수격압의 수압 시계열을 2가지 Reynolds수에서 확보하였다. 모의결과는 pilot 관망체제에서 확보한 실험 자료와 비교하였다. 부정류 마찰항 모형의 매개변수 보정을 위해서 시행착오 방법이 도입되었으며, 부정류 마찰항들을 비교한 결과는 수격압에서 수압이 감쇄되는 과정에 대한 전반적인 이해를 돕고자 하였다. 이와 같은 결과는 관망의 천이류를 적절히 예측하는데 부정류 마찰항의 적절한 고려가 필수적인 부분임을 알려 주고 있다.

• Journal of Microbiology and Biotechnology
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• 제17권4호
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• pp.644-649
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• 2007

Response surface model was developed for predicting the growth rates of Salmonella enterica sv. Typhimurium in tryptic soy broth (TSB) medium as a function of combined effects of temperature, pH, and NaCl. The TSB containing six different concentrations of NaCl (0, 2, 4, 6, 8, and 10%) was adjusted to an initial of six different pH levels (pH 4, 5, 6, 7, 8, 9, and 10) and incubated at 10 or $20^{\circ}C$. In all experimental variables, the primary growth curves were well $(r^2=0.900\;to\;0.996)$ fitted to a Gompertz equation to obtain growth rates. The secondary response surface model for natural logarithm transformations of growth rates as a function of combined effects of temperature, pH, and NaCl was obtained by SAS's general linear analysis. The predicted growth rates of the S. Typhimurium were generally decreased by basic (9, 10) or acidic (5, 6) pH levels or increase of NaCl concentrations (0-8%). Response surface model was identified as an appropriate secondary model for growth rates on the basis of coefficient determination $(r^2=0.960)$, mean square error (MSE=0.022), bias factor $(B_f=1.023)$, and accuracy factor $(A_f=1.164)$. Therefore, the developed secondary model proved reliable predictions of the combined effect of temperature, NaCl, and pH on growth rates for S. Typhimurium in TSB medium.

• Structural Engineering and Mechanics
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• 제83권3호
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• pp.293-304
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• 2022

In this work, a novel reliability approach for combined high and low cycle fatigue (CCF) estimation is developed by combining active learning strategy with least squares support vector machines (LS-SVM) (named as ALS-SVM) surrogate model to address the multi-resources uncertainties, including working loads, material properties and model itself. Initially, a new active learner function combining LS-SVM approach with Monte Carlo simulation (MCS) is presented to improve computational efficiency with fewer calls to the performance function. To consider the uncertainty of surrogate model at candidate sample points, the learning function employs k-fold cross validation method and introduces the predicted variance to sequentially select sampling. Following that, low cycle fatigue (LCF) loads and high cycle fatigue (HCF) loads are firstly estimated based on the training samples extracted from finite element (FE) simulations, and their simulated responses together with the sample points of model parameters in Coffin-Manson formula are selected as the MC samples to establish ALS-SVM model. In this analysis, the MC samples are substituted to predict the CCF reliability of turbine blades by using the built ALS-SVM model. Through the comparison of the two approaches, it is indicated that the reliability model by linear cumulative damage rule provides a non-conservative result compared with that by the proposed one. In addition, the results demonstrate that ALS-SVM is an effective analysis method holding high computational efficiency with small training samples to gain accurate fatigue reliability.

• International Journal of Precision Engineering and Manufacturing
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• 제8권1호
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• pp.3-10
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• 2007

A new approach based on implicit surface interpolation combined with domain decomposition is proposed for filling complex-shaped holes in a large polygon model, A surface was constructed by creating a smooth implicit surface from an incomplete polygon model through which the actual surface would pass. The implicit surface was defined by a radial basis function, which is a continuous scalar-value function over the domain $R^{3}$. The generated surface consisted of the set of all points at which this scalar function is zero. It was created by placing zero-valued constraints at the vertices of the polygon model. The well-known domain decomposition method was used to treat the large polygon model. The global domain of interest was divided into smaller domains in which the problem could be solved locally. The LU decomposition method was used to solve the set of small local problems; the local solutions were then combined using weighting coefficients to obtain a global solution. The validity of this new approach was demonstrated by using it to fill various holes in large and complex polygon models with arbitrary topologies.

• Journal of Information Technology Applications and Management
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• 제15권1호
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• pp.225-242
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• 2008

PM (Inconsistency Pattern Modeling) is a hybrid supervised learning technique using the inconsistence pattern of input variables in mining data sets. The IPM tries to improve prediction accuracy by combining more than two different supervised learning methods. The previous related studies have shown that the IPM was superior to the single usage of an existing supervised learning methods such as neural networks, decision tree induction, logistic regression and so on, and it was also superior to the existing combined model methods such as Bagging, Boosting, and Stacking. The objectives of this paper is explore the characteristics of the IPM. To understand characteristics of the IPM, three experiments were performed. In these experiments, there are high performance improvements when the prediction inconsistency ratio between two different supervised learning techniques is high and the distance among supervised learning methods on MDS (Multi-Dimensional Scaling) map is long.

• 대한기계학회논문집B
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• 제24권4호
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• pp.495-503
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• 2000

The present numerical study investigates flow characteristics and heat transfer enhancement of the viscoelastic non-Newtonian fluid in a 2:1 rectangular duct. The combined effect of temperature-dependent viscosity, buoyancy and secondary flow caused by second normal stress difference are all considered. The Reiner-Rivlin model is used as a viscoelastic fluid model to simulate the secondary flow and temperature-dependent viscosity model is adopted. Three types of thermal boundary conditions involving different combinations of heated walls and adiabatic walls are considered in this study. Calculated Nusselt numbers are in good agreement with experimental results in both the thermal developing and thermally developed regions. The heat transfer enhancement can be explained by the combined viscoelasticity-driven secondary flow, buoyancy-induced secondary flow and temperature-dependent viscosity.