• 콘크리트학회논문집
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• 제18권4호
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• pp.479-487
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• 2006

본 연구는 고성능 콘크리트를 사용한 프리텐션 콘크리트 부재에 대한 시간의존거동해석에 관한 연구이다. 일반 콘크리트의 크리프, 건조수축 및 강재의 릴렉세이션 현상에 대한 기존의 AASHTO 방법을 수정하여, 고성능 콘크리트 부재에 대한 단계-함수법 및 시간-단계법에 의한 시간의존 해석기법을 소개하였다. 제시된 모델은 고성능 콘크리트 프리텐션 부재의 프리스트레스 손실 및 처짐에 대한 초기 및 시간의존거동 예측 값을 제공해 준다. 제안된 모델을 이용하여, 고성능 콘크리트를 사용한 프리텐션 부재의 시간의존거동에 관한 실험 결과와 비교하였다. 기존의 AASHTO 규정에 의한 시간의존 거동 예측치에 비해, 소개된 모델에 의한 고성능 콘크리트 부재의 초기 및 시간의존거동 예측결과가 실제 거동에 보다 정확한 결과를 제공해 주었다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.322-326
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• 2003

In this paper, we establish a new robust $H_{\infty}$ performance condition for uncertain discrete-time systems with convex polytopic uncertainties. We express the condition as a set of linear matrix inequalities (LMIs), which are used to check stability and $H_{\infty}$ disturbance attenuation level by a parameter-dependent Lyapunov matrix. We show that the new condition provides less conservative result than the existing ones which use single Lyapunov matrix. We also show that the robust $H_{\infty}$ state feedback design problem for such uncertain discrete-time systems can be easily dealt with using the approach. The key point in this paper is to propose a kind of decoupling between the Lyapunov matrix and the system matrices in the parameter-dependent matrix inequality by introducing one new matrix variable.

• Structural Monitoring and Maintenance
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• 제2권1호
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• pp.49-64
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• 2015

This paper presents a method for assessing the risk of wave run-up and overtopping of existing coastal defences and for analysing the probability of failure of the structures under future hydraulic conditions. The recent UK climate projections are employed in the investigations of the influence of changing environments on the long-term performance of sea defences. In order to reduce the risk of wave run-up and overtopping caused by rising sea level and to maintain the present-day allowances for wave run-up height and overtopping discharge, the future necessary increase in crest level of existing structures is investigated. Various critical failure mechanisms are considered for reliability analysis, i.e., erosion of crest by wave overtopping, failure of seaside revetment, and internal erosions within earth sea dykes. The time-dependent reliability of sea dykes is analysed to give probability of failure with time. The results for an example earth dyke section show that the necessary increase in crest level is approximately double of sea level rise to maintain the current allowances. The probability of failure for various failure modes of the earth dyke has a significant increase with time under future hydraulic conditions.

• Communications for Statistical Applications and Methods
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• 제31권4호
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• pp.365-375
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• 2024

Diverse methods to evaluate the prediction model of a time to event have been proposed in the context of right censored data where all subjects are subject to be susceptible. A time-dependent AUC (area under curve) measures the predictive ability of a marker based on case group and control one which are varying over time. When a substantial portion of subjects are event-free, a population consists of a susceptible group and a cured one. An uncertain curability of censored subjects makes it difficult to define both case group and control one. In this paper, our goal is to propose a time-dependent AUC for a cure rate model when a censoring distribution is related with covariates. A class of inverse probability of censoring weighted (IPCW) AUC estimators is proposed to adjust the possible sampling bias. We evaluate the finite sample performance of the suggested methods with diverse simulation schemes and the application to the melanoma dataset is presented to compare with other methods.

• 응용통계연구
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• 제32권1호
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• pp.69-81
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• 2019

본 논문에서는 딥러닝을 이용한 이변량 장기종속시계열(long-range dependent time series) 예측을 고려하였다. 시계열 데이터 예측에 적합한 LSTM(long short-term memory) 네트워크를 이용하여 이변량 장기종속시계열을 예측하고 이를 이변량 FARIMA(fractional ARIMA) 모형인 FIVARMA 모형과 VARFIMA 모형과의 예측 성능을 실증 자료 분석을 통해 비교하였다. 실증 자료로는 기능적 자기공명 영상(fMRI) 및 일일 실현 변동성(daily realized volatility) 자료를 이용하였으며 표본외 예측(out-of sample forecasting) 오차 비교를 통해 예측 성능을 측정하였다. 그 결과, FIVARMA 모형과 VARFIMA 모형의 예측값에는 미묘한 차이가 존재하며, LSTM 네트워크의 경우 초매개변수 선택으로 복잡해 보이지만 계산적으로 더 안정되면서 예측 성능도 모수적 장기종속시계열과 뒤지지 않은 좋은 예측 성능을 보였다.

• Journal of the Korean Data and Information Science Society
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• 제19권2호
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• pp.421-429
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• 2008

We consider a general semiparametric additive risk model that consists of three components. They are parametric, purely and smoothly nonparametric components. In parametric component, time dependent term is known up to proportional constant. In purely nonparametric component, time dependent term is an unknown function, and time dependent term in smoothly nonparametric component is an unknown but smoothly function. As an estimation method of this model, we use the weighted least square estimation by Huffer and McKeague (1991). We provide an illustrative example as well as a simulation study that compares the performance of our method with the ordinary least square method.

• 경영과학
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• 제30권1호
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• pp.15-24
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• 2013

We consider the single machine scheduling problem with a rate-modifying activity and time-dependent deterioration after the activity. The class of scheduling problems with rate-modifying activities and the class of scheduling problems with time-dependent processing times have been studied independently. However, the integration of these classes is motivated by human operators of tasks who has fatigue while carrying out the operation of a series of tasks. This situation is also applicable to machines that experience performance degradation over time due to mal-position or mal-alignment of jobs, abrasion of tools, and scraps of operations, etc. In this study, the integration of the two classes of scheduling problems is considered. We present a mathematical model to determine job-sequence and a position of a rate-modifying activity for the integration problem. Since the model is difficult to solve as the size of real problem being very large, we propose genetic algorithms. The performance of the algorithms are compared with optimal solutions with various problems.

• 대한토목학회논문집
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• 제26권1A호
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• pp.237-246
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• 2006

손상된 구조부재, 특히 철근콘크리트교량 교각의 내진성능을 정확하게 평가할 수 있도록 하기 위하여 비탄성 시간종속요소를 제안하였다. 비탄성 시간종속요소는 강도 및 강성의 저하된 상태를 유지한 부재상태에 보수 및 보강에 의한 특성치들의 증가분에 대한 효과를 고려할 수 있는 요소이다. 이 시간종속요소는 활성시작시간과 활성끝시간을 갖는 비탄성 요소로서 정적시간이력해석이나 동적시간이력해석의 경우, 사용자가 원하는 시간간격 내에서 자유롭게 활성화를 시킬 수 있는 장점이 있다. 본 연구에서 개발된 시간종속요소를 이용한 해석결과를 보수 및 보강된 철근콘크리트 교각 실험결과와 비교하였고 전반적으로 만족할만한 상관관계를 얻었다. 아울러 연속지진하중하에서 철근콘크리트 교량의 비선형 시간이력의 비교해석을 통하여 개발된 요소의 타당성을 입증하였다. 결론적으로 본 연구에서 개발된 시간종속요소는 보수 및 보강후의 철근콘크리트교량 교각의 내진수행능력 산정에 유용한 자료를 제공하여 구조물의 전반적인 내진안정성 검토에 크게 기여를 할 수 있을 것으로 사료된다.

• 대한음성학회지:말소리
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• 제53호
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• pp.143-156
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• 2005

Speaker adaptation in eigenvoice space is a popular method for rapid speaker adaptation. To improve the performance of the method, the number of speaker dependent models should be increased and eigenvoices should be re-estimated. However, principal component analysis takes much time to find eigenvoices, especially in a continuous speech recognition system. This paper describes a method to reduce computation time to estimate eigenvoices only for supplementary speaker dependent models and to merge them with the used eigenvoices. Experiment results show that the computation time is reduced by 73.7% while the performance is almost the same in case that the number of speaker dependent models is the same as used ones.

• Computers and Concrete
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• 제19권3호
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• pp.305-313
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• 2017

A robust finite element based reinforced concrete bridge deck corrosion initiation model is applied for time-dependent probabilistic sensitivity analysis. The model is focused on uncertainties in the governing parameters that include variation of high performance concrete (HPC) diffusion coefficients, concrete cover depth, surface chloride concentration, holidays in reinforcements, coatings and critical chloride threshold level in several steel reinforcements. The corrosion initiation risk is expressed in the form of probability over intended life span of the bridge deck. Conducted study shows the time-dependent sensitivity analysis to evaluate the significance of governing parameters on chloride ingress rate, various steel reinforcement protection and the corrosion initiation likelihood. Results from this probabilistic analysis provide better insight into the effect of input parameters variation on the estimate of the corrosion initiation risk for the design of concrete structures in harsh chloride environments.