• 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.

• 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.

• 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.

• 한국물환경학회지
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• 제25권1호
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• pp.26-36
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• 2009

Combined sewer system (CSS) has been built in the most urban areas across the nation. During dry weather conditions, CSS works fine. But during heavy rain storms, combined sewage frequently overflows into the stream. This study simulated the hydrologic cycle and pollutant loads (BOD, SS, TN and TP) in the Mokgamcheon watershed considering combined sewer overflows (CSOs). PC storm water management model (PCSWMM) was used for continuous simulation and CSOs are considered using the flow divider. Sensitivity analysis, calibration and verification for water quantity and quality are carried out. To verify CSOs, field measurements of CSOs are compared with simulated results. As a result, 41.3% of precipitation flows into the stream directly and 1.1% of water supply flows into stream as CSOs. 6.5% of BOD total loads, 12.0% of SS, 13.6% of TP, and 29.2% of TN are from CSOs. This result will be effective to the integrated watershed management for sustainability.

• International Journal of Computer Science & Network Security
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• 제21권7호
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• pp.159-168
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• 2021

Detecting cyber-attacks using machine learning or deep learning is being studied and applied widely in network intrusion detection systems. We noticed that the application of deep learning algorithms yielded many good results. However, because each deep learning model has different architecture and characteristics with certain advantages and disadvantages, so those deep learning models are only suitable for specific datasets or features. In this paper, in order to optimize the process of detecting cyber-attacks, we propose the idea of building a new deep learning network model based on the association and combination of individual deep learning models. In particular, based on the architecture of 2 deep learning models: Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM), we combine them into a combined deep learning network for detecting cyber-attacks based on network traffic. The experimental results in Section IV.D have demonstrated that our proposal using the CNN-LSTM deep learning model for detecting cyber-attacks based on network traffic is completely correct because the results of this model are much better than some individual deep learning models on all measures.

• 지능정보연구
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• 제29권1호
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• pp.377-396
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• 2023

암호화폐시장이 지속해서 성장함에 따라 하나의 새로운 금융시장으로 발전하였다. 이러한 암호화폐시장에 관한 투자전략 연구의 필요성 또한 대두되고 있다. 본 연구에서는 단기매매전략과 딥러닝을 결합한 암호화폐 투자 방법론에 대해 실증분석을 진행하였다. 투자 대상의 암호화폐를 이더리움으로 설정하고, 과거 데이터를 기반으로 최적의 파라미터를 찾아 이를 활용하여 실험 모델의 투자 성과를 분석하였다. 실험 모델은 변동성돌파전략, LSTM(Long Short Term Memory)모델, 이동평균 교차 전략, 그리고 단일 모델들을 결합한 결합 모델이다. 변동성돌파전략은 일 단위로 변동성이 크게 상승할 때 매수하고 당일 종가에 매도하는 단기매매전략이며, LSTM모델은 시계열 데이터에 적합한 딥러닝 모델인 LSTM을 활용하여 얻은 예측 종가를 이용한 매매방법이다. 이동평균 교차 전략은 단기 이동평균선이 교차할 때 매매를 결정하는 방법이다. 결합 모델은 변동성돌파전략의 매수 조건과 변동성돌파전략의 목표 매수가보다 LSTM의 예측 종가가 큰 경우 매수하는 조건이 동시에 만족하면 매수하는 규칙이다. 결합 모델은 변동성돌파전략과 LSTM모델의 파생 변수를 활용해 매수 조건에 AND와 OR를 사용하여 만든 매매 규칙이다. 실험 결과, 단일 모델보다 결합 모델에서 투자 성과가 우수함을 확인하였다. 특히, 데일리 트레이딩과 매수 후 보유의 누적수익률은 -50%이하인 것에 비해 결합 모델은 +11.35%의 높은 누적수익률을 달성하여 하락이 지속되던 투자 기간에도 기술적으로 방어하며 수익을 낼 수 있음을 확인하였다. 본 연구는 기존의 딥러닝기반 암호화폐 가격 예측에서 나아가 변동성이 큰 암호화폐시장에서 딥러닝과 단기매매전략을 결합하여 투자 성과를 개선하였다는 점에서 학술적 의의가 있으며, 실제 투자 시 적용 가능성을 보여주었다는 점에서 실무적 의의가 있다.

• 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.

• 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.

• 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.

• Structural Engineering and Mechanics
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• 제84권5호
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• pp.591-604
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• 2022

A gravity wall combined with an anchoring lattice frame (a combined retaining structure) is adopted at a typical engineering site at Dali-Ruili Railway Line China. Where, the combined retaining structure supports a soil deposit covering on different inclined rock slopes. With an aim to investigate and compare the effects of inclined rock slopes on the response of combined retaining structure under seismic excitation, three groups of shaking table tests are conducted. The rock slopes are shaped as planar surfaces inclined at angles of 20°, 30°, and 40° with the horizontal, respectively. The shaking table tests are supplemented by dynamic numerical simulations. The results regarding the horizontal acceleration response, vertical acceleration response, permanent displacement mode, and axial anchor force are comparatively examined. The acceleration response is more susceptible to outer structural profile of combined retaining structure than to inclined angle of rock slope. The permanent displacement decreases when the inclined angle of the rock slope increases within a range of 20°-40°. A critical inclined angle of rock slope exists within a range of 20°-40°, and induces the largest axial anchor force in the combined retaining structure.