• Journal of the Korea Concrete Institute
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• v.18 no.4 s.94
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• pp.479-487
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• 2006

This paper deals with a research about the time-dependent behavior analysis for pre-tensioned high-performance concrete(HPC) members. By improving AASHTO-LRFD(2004) method for predicting the creep and shrinkage of normal concrete, and the relaxation of prestressing tendon, a time-dependent behavior analysis of high-performance concrete structures has been introduced. Two methods, the step-function method and the time-step method have been incorporated in the time-dependent analysis. The developed program can predict the initial and time-dependent losses of prestressing forces and the deflections of high-performance concrete structures. The present model has been verified by comparing with the experimental results from the test of time-dependent behaviors of pre-tensioned members using high-performance concrete. From this, the current model gives good relations with the experimental results, but the AASHTO method is not good for the prediction of time-dependent behaviors of high-performance concrete members.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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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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• v.2 no.1
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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.

• The Korean Journal of Applied Statistics
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• v.32 no.1
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• pp.69-81
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• 2019

We consider bivariate long range dependent (LRD) time series forecasting using a deep learning method. A long short-term memory (LSTM) network well-suited to time series data is applied to forecast bivariate time series; in addition, we compare the forecasting performance with bivariate fractional autoregressive integrated moving average (FARIMA) models. Out-of-sample forecasting errors are compared with various performance measures for functional MRI (fMRI) data and daily realized volatility data. The results show a subtle difference in the predicted values of the FIVARMA model and VARFIMA model. LSTM is computationally demanding due to hyper-parameter selection, but is more stable and the forecasting performance is competitively good to that of parametric long range dependent time series models.

• Journal of the Korean Data and Information Science Society
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• v.19 no.2
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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.

• Korean Management Science Review
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• v.30 no.1
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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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1A
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• pp.237-246
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• 2006

In order to evaluate the seismic performance of damaged reinforced concrete members, particularly bridge piers, an inelastic time-dependent element is proposed. The proposed element enables increased characteristics due to structural intervention(i.e., repair or retrofitting) to be accurately reflected to the degraded strength and stiffness of the members. The inelastic time-dependent element having both birth and death time can freely be activated within the user-defined time intervals during static and dynamic time-history analysis. Comparative studies are carried out for reinforced concrete bridge piers that are repaired and retrofitted. Analytical predictions using the developed element show reasonable correlation with experimental results. Also conducted is a nonlinear time-history analysis of a reinforced concrete bridge under multiple earthquakes. The comparative analytical results prove the validation of current development. In all, it is concluded that the present element is capable of providing salient features for the healthy evaluation of seismic performance and hence seismic stability assessment of RC bridge piers being repaired and retrofitted.

• MALSORI
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• no.53
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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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• v.19 no.3
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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.

• International Journal of Control, Automation, and Systems
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• v.5 no.2
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• pp.170-183
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• 2007

This paper presents a delay-dependent approach to robust filtering for linear parameter-varying (LPV) systems with discrete and distributed time-invariant delays in the states and outputs. It is assumed that the state-space matrices affinely depend on parameters that are measurable in real-time. Some new parameter-dependent delay-dependent stability conditions are established in terms of linear matrix inequalities (LMIs) such that the filtering process remains asymptotically stable and satisfies a prescribed $H_{\infty}$ performance level. Using polynomially parameter-dependent quadratic (PPDQ) functions and some Lagrange multiplier matrices, we establish the parameter-independent delay-dependent conditions with high precision under which the desired robust $H_{\infty}$ filters exist and derive the explicit expression of these filters. A numerical example is provided to demonstrate the validity of the proposed design approach.