• Proceedings of the Korea Concrete Institute Conference
• /
• 2009.05a
• /
• pp.43-44
• /
• 2009

3D bridge information models for a concrete box-girder bridge were built and a typical application example for the estimation linked with the 3D models was proposed. 3D geometry objects with PBS (product breakdown structure) were constructed using standard classification codes and 2D drawings. Information on the amount of materials according to the classification codes was utilized for the estimation system. A process for the estimation of concrete and rebars was developed and verified through the pilot test. Optimization of rebar fabrication was suggested as an additional function and was utilized for the cost reduction and standard fabrication.

• Journal of the Korean Data and Information Science Society
• /
• v.24 no.1
• /
• pp.33-39
• /
• 2013

In the transformation of response variable in partial linear models outliers can cause a bad effect on estimating the transformation parameter, just as in the linear models. To solve this problem the processes of estimating transformation parameter and detecting outliers are needed, but have difficulties to be performed due to the arbitrariness of the nonparametric function included in the partial linear model. In this study, through the estimation of nonparametric function and outlier detection methods such as a sequential test and a maximum trimmed likelihood estimation, processes for transforming response variable robust to outliers in partial linear models are suggested. The proposed methods are verified and compared their effectiveness by simulation study and examples.

• Computers and Concrete
• /
• v.4 no.1
• /
• pp.1-18
• /
• 2007

Over the past decades, an enormous amount of effort has been expended in laboratory and field studies on concrete durability estimation. The results of this research are still either widely scattered in the journal literature or mentioned briefly in the standard textbooks. Moreover, the theoretical approaches of deterioration mechanisms with a predictive character are limited to some complicated mathematical models not widespread in practice. A significant step forward could be the development of appropriate software for computer-based estimation of concrete service life, including reliable mathematical models and adequate experimental data. In the present work, the basis for the development of a computer estimation of the concrete service life is presented. After the definition of concrete mix design and structure characteristics, as well as the consideration regarding the environmental conditions where the structure will be found, the concrete service life can be reliably predicted using fundamental mathematical models that simulate the deterioration mechanisms. The prediction is focused on the basic deterioration phenomena of reinforced concrete, such as carbonation and chloride penetration, that initiate the reinforcing bars corrosion. Aspects on concrete strength and the production cost are also considered. Field observations and data collection from existing structures are compared with predictions of service life using the above model. A first attempt to develop a database of service lives of different types of reinforced concrete structure exposed to varying environments is finally included.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.2
• /
• pp.438-455
• /
• 2024

Recently, many unsupervised learning-based models have emerged for Just Noticeable Difference (JND) estimation, demonstrating remarkable improvements in accuracy. However, these models suffer from a significant drawback is that their heavy reliance on handcrafted priors for guidance. This restricts the information for estimating JND simply extracted from regions that are highly related to handcrafted priors, while information from the rest of the regions is disregarded, thus limiting the accuracy of JND estimation. To address such issue, on the one hand, we extract the information for estimating JND in an Adversarial Complementary Learning (ACoL) way and propose an ACoL-JND network to estimate the JND by comprehensively considering the handcrafted priors-related regions and non-related regions. On the other hand, to make the handcrafted priors richer, we take two additional priors that are highly related to JND modeling into account, i.e., Patterned Masking (PM) and Contrast Masking (CM). Experimental results demonstrate that our proposed model outperforms the existing JND models and achieves state-of-the-art performance in both subjective viewing tests and objective metrics assessments.

• Journal of Korean Society of Transportation
• /
• v.5 no.2
• /
• pp.97-112
• /
• 1987

The objective of this study is to construct not only trip production and attraction in Pusan but also to study and examine appropriateness of the model positively. Depending on the estimation models of trip production and attraction of each zone that have been constructed in this study, it has been proved that the formula of multiple regression by the explanation variables like the indices of total employees, total students, floor spaces of residentials and floor spaces of educational and cultural areas within the study areas have very high explanatory capacity and appropriateness. It si considered that a study of method on new division, integration or omission etc. of the existing zones preceeding for reduction of calculation quantity and a study of estimation error have to be done for future study, if these models are used actually.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.9 no.2
• /
• pp.112-118
• /
• 2000

This paper deals with the application of sensitivity method to the parameter estimation for the dynamic analysis of gener-al mechanical system. In this procedure we take the derivatives of the given system with respect to a certain parameter and use this information to implement the steepest descent method. This paper will give two examples of this technique applied to simple vehicle models. This paper will give two examples of this technique applied to simple vehicle models. Simulation results show excellent convergence and accuracy of parameter estimates.

• Journal of Korean Society for Quality Management
• /
• v.26 no.3
• /
• pp.130-140
• /
• 1998

Studies present a guide to parameter estimation of software reliability models using SAS JMP. In this paper, we consider only software reliability growth model(SRGM), where mean value function has a S-shaped growth curve, such as Yamada et al. model, and ohba inflection model. Besides these stochastic SRGM, deterministic SRGM's, by fitting Logistic and Gompertz growth curve, have been widely used to estimate the error content of software systems. Introductions or guide lines of JMP are concerned. Estimation of parameters of Yamada et al. model and Logistic model is accomplished by using JMP. The differences between Yamada et al. model and Logistic model is accomplished by using JMP. The differences between Yamada et al. model and Logistic model is discussed, along with the variability in the estimates or error sum of squares. This paper have shown that JMP can be an effective tool I these research.

• The Korean Journal of Applied Statistics
• /
• v.21 no.5
• /
• pp.783-789
• /
• 2008

We investigate the effects of the misspecification of cointegrating(CI) ranks at other frequencies on the inference of seasonal models at the frequency of interest; our study includes tests for CI ranks and estimation of CI vectors. Earlier studies focused mostly on a single frequency corresponding to one seasonal root at a time, ignoring possible cointegration at the remaining frequencies. We investigate the effects of the mis-specification, especially in finite samples, by adopting Gaussian reduced rank(GRR) estimation by Ahn and Reinsel (1994) that considers cointegration at all frequencies of seasonal unit roots simultaneously. It is observed that the identification of the seasonal CI rank at the frequency of interest is sensitive to the mis-prespecification of the CI ranks at other frequencies, mainly when the CI ranks at the remaining frequencies are underspecified.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.1765-1770
• /
• 2005

Recently, particle filters have attracted attentions for nonlinear state estimation. In this approaches, a posterior probability distribution of the state variable is evaluated based on observations in simulation using so-called importance sampling. We proposed a new filter, Evolution Strategies based particle (ESP) filter to circumvent degeneracy phenomena in the importance weights, which deteriorates the filter performance, and apply it to simultaneous state and parameter estimation of nonlinear state space models. Results of numerical simulation studies illustrate the applicability of this approach.

• Journal of Korean Society on Water Environment
• /
• v.21 no.6
• /
• pp.575-583
• /
• 2005

In this study the flow curve estimation is discussed using TANK model which is one of hydrologic models. The main interest is the accuracy of TANK model parameter estimation with respect to the sampling frequency of input data. For doing this, input data with various sampling frequencies is used to estimate model parameters. As a result, in order to generate relatively accurate flow curve, it is recommendable to measure stream flow at least every 8 days.