• Smart Structures and Systems
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• v.25 no.5
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• pp.593-604
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• 2020

Temperature may have more significant influences on structural responses than operational loads or structural damage. Therefore, a comprehensive understanding of temperature distributions has great significance for proper design and maintenance of bridges. In this study, the temperature distribution of the steel box girder is systematically investigated based on the structural health monitoring system (SHMS) of the Sutong Cable-stayed Bridge. Specifically, the characteristics of the temperature and temperature difference between different measurement points are studied based on field temperature measurements. Accordingly, the probability density distributions of the temperature and temperature difference are calculated statistically, which are further described by the general formulas. The results indicate that: (1) the temperature and temperature difference exhibit distinct seasonal characteristics and strong periodicity, and the temperature and temperature difference among different measurement points are strongly correlated, respectively; (2) the probability density of the temperature difference distribution presents strong non-Gaussian characteristics; (3) the probability density function of temperature can be described by the weighted sum of four Normal distributions. Meanwhile, the temperature difference can be described by the weighted sum of Weibull distribution and Normal distribution.

• International Journal of Highway Engineering
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• v.19 no.5
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• pp.89-96
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• 2017

PURPOSES: This study aims to develop a rational procedure for estimating the pavement roughness index considering vehicle wandering. METHODS : The location analysis of the passing vehicle in the lane was performed by approximately 1.2 million vehicles for verification of the wandering distribution. According to verification result, the distribution follows the normal distribution pattern. The probability density function was estimated using each lane's wandering distribution model. Then the procedure for applying a weighted value into the lane profile was conducted using this function. RESULTS : The modified index, MRIw, with consideration towards applying the wandering weighted value application was computed then compared with MRI. It was found that the Coefficient of Variation for distribution of lateral roughness index in the lane was high in the case of a large difference between each index (i.e., MRIw and MRI) observed. CONCLUSIONS : This result confirms that the new procedure with consideration of the weight factor can successfully improve the lane representative characteristics of the roughness index.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.4
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• pp.151-161
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• 1993

The log-Gumbel distribution in real space is defined by transforming the conventional log-Gumbel distribution in log space. For this model, the parameter estimation techniques are applied based on the methods of moments, maximum likelihood and probability weighted moments. The asymptotic variances of estimator of the quantiles for each estimation method are derived to find the confidence limits for a given return period. Finally, the log-Gumbel model is applied to actual flood data to estimate the parameters, quantiles and confidence limits.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.4
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• pp.141-150
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• 1993

For the three parameter Weibull distribution, the parameter estimation techniques are applied and the asymptotic variances of the quantile to obtain the confidence limits for a given return period are derived. Three estimation techniques are used for these purposes: the methods of moments, maximum likelihood and probability weighted moments. The three parameter Weibull distribution as a flood frequency model is applied to actual flood data.

• Journal of the Korean Data and Information Science Society
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• v.15 no.1
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• pp.227-237
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• 2004

In this paper we presented a Bayesian inference approach for estimating the location and scale parameters of the lognormal distribution using iterative Gibbs sampling algorithm. We also presented estimation of location parameter by two non iterative methods, importance sampling and weighted bootstrap assuming scale parameter as known. The estimates by non iterative techniques do not depend on the specification of hyper parameters which is optimal from the Bayesian point of view. The estimates obtained by more sophisticated Gibbs sampler vary slightly with the choices of hyper parameters. The objective of this paper is to illustrate these tools in a simpler setup which may be essential in more complicated situations.

• The Journal of the Acoustical Society of Korea
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• v.22 no.3
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• pp.188-193
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• 2003

Regardless of the distribution of the adaptation data in the testing environment, model-based adaptation methods that have so far been reported in various literature incorporates the adaptation data undiscriminatingly in reducing the mismatch between the training and testing environments. When the amount of data is small and the parameter tying is extensive, adaptation based on outlier data can be detrimental to the performance of the recognizer. The distribution of the adaptation data plays a critical role on the adaptation performance. In order to maximally improve the recognition rate in the testing environment using only a small number of adaptation data, supervised weighted training is applied to the structural maximum a posterior (SMAP) algorithm. We evaluate the performance of the proposed weighted SMAP (WSMAP) and SMAP on TIDIGITS corpus. The proposed WSMAP has been found to perform better for a small amount of data. The general idea of incorporating the distribution of the adaptation data is applicable to other adaptation algorithms.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.2
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• pp.51-59
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• 2017

Due to the rapid change of global business environment, the growth of China's steel industry and the inflow of cheap products, domestic steel industry is faced on downward trend. The change of business paradigms from a quantitative growth to a qualitative product is needed in this steel industry. In this environment, it is very important for domestic steel distribution companies to secure their competitiveness by selecting good supply companies through a efficient procurement strategy and effective method. This study tried to find out the success factors of steel distribution industry based on survey research from experts. Weighted values of each factors were found by using AHP (analytic hierarchy process) analysis. The weighted values were applied to DEA(data envelopment analysis) model and eventually the best steel supply company were selected. This paper used 29 domestic steel distribution firms for case example and 5 steps of decision process to select good vendors were suggested. This study used quality, price, delivery and finance as a selection criteria. Using this four criterions, nine variable were suggested. Which were product diversity, base price, discount, payment position, average delivery date, urgency order responsibility and financial condition. These variables were used as a output variable of DEA. Sales and facilities were used as an input variable. Pairwise comparison was conducted using these variables. The weighted value calculated by AHP pairwise comparison were used for DEA analysis. Through the analysis of DEA efficiency process, good DMU (decision making unit) were recommended as a steel supply company. The domestic case example was used to show the effectiveness of this study.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.977-985
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• 2021

The main aim of the study is to provide empirical evidence about the association between stock market exchange data and weighted price index. This research utilized monthly reported data from the Amman stock exchange market (ASE) and the Central Bank of Jordan (CBJ). The weighted price index was employed as the dependent variable and the independent variables were weighted price index (WPI), turnover ratio (TOR), number of trading days (NTD), price-earnings ratio (PER), and dividends yield ratio (DY). The time period of the study was from January 2015 to October 2020. The study's methodology follows a quantitative approach using the multiple regression method to test the hypotheses of the study. The final results of the study provided conclusive evidence that the market-weighted price index is strongly and positively correlated to three predetermined variables, namely; turnover ratio, price-earnings ratio, and dividend yield but no evidence was obtained for the effect of the number of trading days. The finding of the current study proved that the market price index is not only influenced by macro factors, but also by other variables assumed to not beneficial for the judgment of price index movements.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.12 no.3
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• pp.69-75
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• 2013

During the magnetic abrasive polishing of a curved surface, the improvement in surface roughness varies with the maximum value and distribution of magnetic flux density. Thus, in this study, the magnetic flux density on the curved surface was simulated according to curvature radii of magnetic tool. As a result of the simulation, the 14.5mm of the magnetic tool had a higher maximum magnetic flux density and it showed a large weighted magnetic flux density. The weighted magnetic flux density means the highest value for the magnetic flux density in the curvature of the magnetic tool. From the experimental verification, the better improvement in surface roughness was observed on wider area at the 14.5mm radius of the magnetic tool than other radii.

• Journal of the Korea Safety Management & Science
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• v.3 no.3
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• pp.175-190
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• 2001

We propose, a new process capability index $C_{psk}$(WV) applying the weighted variance control charting method for non-normally distributed. The main idea of the weighted variance method(WVM) is to divide a skewed or asymmetric distribution into two normal distributions from its mean to create two new distributions which have the same mean but different standard deviations. In this paper we propose an example, a distributions generated from the Johnson family of distributions, to demonstrate how the weighted variance-based process capability indices perform in comparison with another two non-normal methods, namely the Clements and the Wright methods. This example shows that the weighted valiance-based indices are more consistent than the other two methods in terms of sensitivity to departure to the process mean/median from the target value for non-normal processes. Second method show using the percentage nonconforming by the Pearson, Johnson and Burr systems. This example shows a little difference between the Pearson system and Burr system, but Johnson system underestimated than the two systems for process capability.