• Earthquakes and Structures
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• v.20 no.1
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• pp.97-107
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• 2021

A comprehensive study on seismic performance of wood frame building in hilly regions is presented. Specifically, seismic fragility assessment of a typical wood frame building at various locations of the northeast region of India are demonstrated. A three-dimensional simplified model of the wood frame building is developed with due consideration to nonlinear behaviour of shear walls under lateral loads. In doing so, a trilinear model having improved capability to capture the force-deformation behaviour of shear walls including the strength degradation at higher deformations is proposed. The improved capability of the proposed model to capture the force-deformation behaviour of shear wall is validated by comparing with the existing experimental results. The structural demand values are obtained from nonlinear time history analysis (NLTHA) of the three-dimensional wood frame model considering the effect of uncertainty due to record to record variation of ground motions and structural parameters as well. The ground motion bins necessary for NLTHA are prepared based on the identified hazard level from probabilistic seismic hazard analysis of the considered locations. The maximum likelihood estimates of the lognormal fragility parameters are obtained from the observed failure cases and the seismic fragilities corresponding to different locations are estimated accordingly. The results of the numerical study show that the wood frame constructions commonly found in the region are likely to suffer minor cracking or damage in the shear walls under the earthquake occurrence corresponding to the estimated seismic hazard level; however, poses negligible risk against complete collapse of such structures.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.4
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• pp.75-88
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• 2008

This paper presents a spatial-level nonparametric multi-focus image fusion technique based on kernel estimates of input image blocks' underlying class-conditional probability density functions. Image fusion is approached as a classification task whose posterior class probabilities, P($wi{\mid}Bikl$), are calculated with likelihood density functions that are estimated from the training patterns. For each of the C input images Ii, the proposed method defines i classes wi and forms the fused image Z(k,l) from a decision map represented by a set of $P{\times}Q$ blocks Bikl whose features maximize the discriminant function based on the Bayesian decision principle. Performance of the proposed technique is evaluated in terms of RMSE and Mutual Information (MI) as the output quality measures. The width of the kernel functions, ${\sigma}$, were made to vary, and different kernels and block sizes were applied in performance evaluation. The proposed scheme is tested with C=2 and C=3 input images and results exhibited good performance.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.1
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• pp.59-66
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• 2013

In this paper, we propose a probabilistic framework for model-based clustering of direction of arrival (DOA) data to obtain stable sound source localization (SSL) estimates. Model-based clustering has been shown capable of handling highly overlapped and noisy datasets, such as those involved in DOA detection. Although the Gaussian mixture model is commonly used for model-based clustering, we propose use of the von Mises mixture model as more befitting circular DOA data than a Gaussian distribution. The EM framework for the von Mises mixture model in a unit hyper sphere is degenerated for the 2D case and used as such in the proposed method. We also use a histogram of the dataset to initialize the number of clusters and the initial values of parameters, thereby saving calculation time and improving the efficiency. Experiments using simulated and real-world datasets demonstrate the performance of the proposed method.

• Journal of Families and Better Life
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• v.10 no.1 s.19
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• pp.131-138
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• 1992

Regression analysis has become a standard statistical tool in the behavioral science. Because of its widespread popularity. regression has been often misused. Such is the case when the dependent variable is a qualitative measure rather than a continuous, interval measure. Regression estimates with a qualitative dependent variable does not meet the assumptions underlying regression. It can lead to serious errors in the standard statistical inference. Logit model is recommended as alternatives to the regression model for qualitative dependent variables. Researchers can employ this model to measure the relationship between independent variables and qualitative dependent variables without assuming that logit model was derived from probabilistic choice theory. Coefficients in logit model are typically estimated by the method of Maximum Likelihood Estimation in contrast to ordinary regression model which estimated by the method of Least Squares Estimation. Goodness of fit in logit model is based on the likelihood ratio statistics and the t-statistics is used for testing the null hypothesis.

• Journal of the Korea Institute of Building Construction
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• v.11 no.1
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• pp.91-99
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• 2011

Bayesian network is a form of probabilistic graphical model. It incorporates human reasoning to deal with sparse data availability and to determine the probabilities of uncertain cases. In this research, bayesian network is adopted to model the problem of construction project cost. General information, time, cost, and material, the four main factors dominating the characteristic of construction costs, are incorporated into the model. This research presents verify a model that were conducted to illustrate the functionality and application of a decision support system for predicting the costs. The Markov Chain Monte Carlo (MCMC) method is applied to estimate parameter distributions. Furthermore, it is shown that not all the parameters are normally distributed. In addition, cost estimates based on the Gibbs output is performed. It can enhance the decision the decision-making process.

• Journal of Ocean Engineering and Technology
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• v.25 no.3
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• pp.1-10
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• 2011

This paper estimates the residual longitudinal strength of a damaged double hull VLCC (Very Large Crude Carrier) under combined vertical and horizontal bending moments using Smith's method. The damage estimated in this study occurred due to collision or grounding accidents. The effects of the randomness of the yield stress, plate thickness, extent of damage, and the combination of these three parameters on the ultimate hull girder strength were investigated. Random variables were generated by a Monte Carlo simulation and applied to the double hull VLCC described by the ISSC (International Ship and Offshore Structures Congress) 2000 report.

• Journal of the Korean Operations Research and Management Science Society
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• v.14 no.1
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• pp.97-107
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• 1989

In this study three types of aggregation methods such as the Estimate-Talk-Consensus (ETC) process, the Estimate-Talk-Estimate (ETE) process, and as a new approach the Estimate-Talk-Leader's Estimate (ETLE) process are compared to find which one of the three group processes considered is more effective than others. We, also, investigate the effect of group size on the performance of the group processes. Some experiments were conducted. It was shown that both the ETC and the ETLE processes performed better than the ETE process in approaching correct estimates in this judgmental task. As the size group increased, only the ETC and the ETC processes were shown to result in positive effect.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.204-206
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• 2009

Opportunistic scheduling is one of the important techniques to maximize multiuser diversity gain. In this paper, we propose a distributed opportunistic scheduling scheme for ad-hoc network. In the proposed distributed scheduling scheme, each receiver estimates channel condition and calculates independently its own priority with probabilistic manner, which can reduce excessive probing overhead required to gather the channel conditions of all receivers. We evaluate the proposed scheduling using extensive simulation and simulation results show that proposed scheduling obtains higher network throughput than conventional scheduling schemes and has a flexibility to control the fairness and throughput by controlling the system parameter.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.12
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• pp.2262-2264
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• 2007

In this paper, we propose a distributed opportunistic scheduling scheme for wireless LAN network. Proportional fair scheduling is one of the opportunistic scheduling schemes and used for centralized networks, whereas we design distributed proportional fair scheduling (DPFS). In the proposed DPFS scheme, each receiver estimates channel condition and calculates independently its own priority with probabilistic manner, which can reduce excessive probing overhead required to gather the channel conditions of all receivers. We evaluate the proposed DPFS using extensive simulation and simulation results show that DPFS obtains up to 23% higher throughput than conventional scheduling schemes and has a flexibility to control the fairness and throughput by controlling the system parameter.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.4 no.3
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• pp.93-98
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• 1984

The paper presents an application of the Theory of Queue to a typical eath-haul operations. Field measurements of arrival and serve times were used to analyze the mathematical model for determination of optimal equipment requirements. Despite the model produces somewhat uder estimates of production, the use of the model in solving operation design problems was. found satisfactory on the practical basis.