• Smart Structures and Systems
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• v.21 no.5
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• pp.601-609
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• 2018

The estimated probabilistic model of wind data based on the conventional approach may have high discrepancy compared with the true distribution because of the uncertainty caused by the instrument error and limited monitoring data. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method has been developed in the companion paper and is conducted to formulate the joint probability density function (PDF) of wind speed and direction using the wind monitoring data of the investigated bridge. The established bivariate model of wind speed and direction only represents the features of available wind monitoring data. To characterize the stochastic properties of the wind parameters with the subsequent wind monitoring data, in this study, Bayesian inference approach considering the uncertainty is proposed to update the wind parameters in the bivariate probabilistic model. The slice sampling algorithm of Markov chain Monte Carlo (MCMC) method is applied to establish the multi-dimensional and complex posterior distribution which is analytically intractable. The numerical simulation examples for univariate and bivariate models are carried out to verify the effectiveness of the proposed method. In addition, the proposed Bayesian inference approach is used to update and optimize the parameters in the bivariate model using the wind monitoring data from the investigated bridge. The results indicate that the proposed Bayesian inference approach is feasible and can be employed to predict the bivariate distribution of wind speed and direction with limited monitoring data.

• Steel and Composite Structures
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• v.27 no.4
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• pp.525-536
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• 2018

This paper focuses on the application of the first-order shear deformation theory (FSDT) to thermo-elastic static problems of functionally graded carbon nanotubes reinforced composite (FG-CNTRC) cylindrical pressure vessels. A symmetric displacement field is considered as unknown function along the longitudinal direction, whereas a linear distribution is assumed along the thickness direction. The cylindrical pressure vessels are subjected to an inner and outer pressure under a temperature increase. Different patterns of reinforcement are applied as distribution of CNTs. The effective material properties of FG-CNTRC cylindrical pressure vessels are measured based on the rule of mixture, whereas the governing equations of the problem are here derived through the principle of virtual works. A large parametric investigation studies the effect of some significant parameters, such as the pattern and volume fraction of CNTs, on the longitudinal distribution of deformation, strain and stress components, as useful tool for practical engineering applications.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.10
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• pp.2396-2402
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• 2015

Air compressor, as an essential equipment used in the factory and plant operations, accounts for around 30% of the total electricity consumption in U.S.A, thereby being proposed advanced technologies to reduce electricity consumption. When the fluctuation of the compressed airflow rate is small, the system stability is increased followed by the reduction of the electricity consumption which results in the efficient design of the energy system. In the statistical analysis, the normal distribution, log normal distribution, gamma distribution or the like are generally used to identify system characteristics. However a single distribution may not fit well the data with long tail, representing sudden air flow rate especially in extremes. In this paper, authors decouple the compressed airflow rate into two parts to present a mixture of distribution function and suggest a method to reduce the electricity consumption. This reduction stems from the fact that a general pareto distribution estimates more accurate quantile value than a gaussian distribution when an airflow rate exceeds over a large number.

• KIEAE Journal
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• v.6 no.2
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• pp.51-57
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• 2006

With people's awareness of environment-friendly buildings recently increasing, there is a need to develop environment-friendly construction materials to reduce indoorair pollution levels. Thus, efforts to develop loess finishing materials that can replace the finishing materials currently being used (e.g., gypsum boards and chemical products) are underway. An analysis of the characteristics of domestic loess products,however, revealed that the cracks on loess products can be lessened and their strength can be improved by adding chemical ingredients to them. Thus, this research sought to use 100% natural materials and to develop loess finishing materials. In the experiments that were conducted in this study, appropriate mixture ratios of loess and sand/silica sand were found, and cracks and contraction ratio changes in samples were analyzed by differentiating the ratios of natural ingredients, such as lime, fine jute threads, gypsum, and jute cuttings. Loess'particle size distribution was found to have a high correlation with loess decoration, and it was discovered that the mixture of lime and fine chute threads could improve the contraction ratio. Through this study, which made use of natural ingredients, environment-friendly construction materials that can exercise the original function of loess were developed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.821-829
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• 2006

Traffic load comprise primary input to pavement design causing pavement damage. therefore it should be proceeded suitable traffic load distribution modeling for pavement design and analysis. Traffic load have been represented by equivalent single axle loads (ESALs) which convert mixed traffic stream into one value for design purposes. But there are some limit to apply ESALs to other roads because it is empirical value developed as part of the original AASHO(American Association of State Highway Officials) road test. There have been many efforts to solve these problems. Several leading country have implemented M-E(Mechanistic-Empirical) design procedures based on mechanical concept. As a result, they established traffic load quantification method using load distribution model known as Axle Load Spectra. This paper details Axle Load Spectra and presents axle load distribution model based on normal mixture distribution function using truck load data collected by WIM system installed in national highway. Axle load spectra and axle load distribution model presented in this paper could be useful for basic data when making traffic load quantification plan for pavement design, overweight vehicle permit plan and pavement maintenance cost plan.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.22 no.1
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• pp.51-56
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• 2012

In the present study, we investigated the effect of mechanical alloying (MA) on the formation of amorphous VCo system through solid state reaction during ball milling. Two types of powder samples, ${\sigma}$-VCo intermetallic compound and $V_{50}Co_{50}$ powder mixture, were applied as a starting materials. With increasing milling time, a structural characteristics into the amorphous state is distinctly observed from the structural factor and radial distribution by X-ray diffraction. Amorphization has been observed in all two types of samples after the milling for 120 hrs. DSC spectrum of $V_{50}Co_{50}$ powder sample milled for 60 hrs indicates a sharp exothermic peak from the crystallization at $600^{\circ}C$. The structure factor, S(Q) and radial distribution function, RDF(r), observed by X-ray diffraction gradually change into a structure characteristic of an amorphous state with increasing MA time.

• Journal of Biomedical Engineering Research
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• v.26 no.4
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• pp.223-230
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• 2005

This paper presents a new approach to investigate spatial correlation between independent components of brain alpha activity in functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). To avoid potential problems of simultaneous fMRI and EEG acquisitions in imaging pure alpha activity, data from each modality were acquired separately under a 'three conditions' setup where one of the conditions involved closing eyes and relaxing, thus making it conducive to generation of alpha activity. The other two conditions -- eyes open in a lighted room or engaged in a mental arithmetic task, were designed to attenuate alpha activity. Using a Mixture Density Independent Component Analysis (MD-ICA) that incorporates flexible non-linearity functions into the conventional ICA framework, we could identify the spatiotemporal components of fMRI activations and EEG activities associated with the alpha rhythm. Then, the sources of the individual EEG alpha activity component were localized by a Maximum Entropy (ME) method that is specially designed to find the most probable dipole distribution minimizing the localization error in sense of LMSE. The resulting active dipoles were spatially transformed to 3D MRls of the subject and compared to fMRI alpha activity maps. A good spatial correlation was found in the spatial distribution of alpha sources derived independently from fMRI and EEG, suggesting the proposed method can localize the cortical areas responsible for generating alpha activity successfully in either fMRI or EEG. Finally a functional connectivity analysis was applied to show that alpha activity sources of both modalities were also functionally connected to each other, implying that they are involved in performing a common function: 'the generation of alpha rhythms'.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.6
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• pp.1294-1301
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• 2014

In this paper, separate probabilistic distribution models for voiced and unvoiced speech are estimated and utilized to improve speaker recognition performance. Also, in addition to the conventional mel-frequency cepstral coefficient, skewness, kurtosis, and harmonic-to-noise ratio are extracted and used for voiced speech intervals. Two kinds of scores for voiced and unvoiced speech are linearly fused with the optimal weight found by exhaustive search. The performance of the proposed speaker recognizer is compared with that of the conventional recognizer which uses mel-frequency cepstral coefficient and a unified probabilistic distribution function based on the Gassian mixture model. Experimental results show that the lower the number of Gaussian mixture, the greater the performance improvement by the proposed algorithm.

• Structural Engineering and Mechanics
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• v.62 no.4
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• pp.507-517
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• 2017

Due to the discontinuous nature of uncertainty quantification in conventional evidence theory(ET), the computational cost of reliability analysis based on ET model is very high. A novel ET model based on fuzzy distribution and the corresponding combination rule to synthesize the judgments of experts are put forward in this paper. The intersection and union of membership functions are defined as belief and plausible membership function respectively, and the Murfhy's average combination rule is adopted to combine the basic probability assignment for focal elements. Then the combined membership functions are transformed to the equivalent probability density function by a normalizing factor. Finally, a reliability analysis procedure for structures with the mixture of epistemic and aleatory uncertainties is presented, in which the equivalent normalization method is adopted to solve the upper and lower bound of reliability. The effectiveness of the procedure is demonstrated by a numerical example and an engineering example. The results also show that the reliability interval calculated by the suggested method is almost identical to that solved by conventional method. Moreover, the results indicate that the computational cost of the suggested procedure is much less than that of conventional method. The suggested ET model provides a new way to flexibly represent epistemic uncertainty, and provides an efficiency method to estimate the reliability of structures with the mixture of epistemic and aleatory uncertainties.

• Journal of Physiology & Pathology in Korean Medicine
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• v.33 no.2
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• pp.89-101
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• 2019

In recent times, the number of men with late-onset hypogonadism has increased, and interest on this topic has also increased. This study was conducted to investigate effects of the mixture extract of Fructus amomi Amari, Eucommiae cortex, Bombyx batryticatus on improve late-onset hypogonadism. The experimental subjects consisted of three groups: a control group consisting of 8-week-old male ICR mice that had undergone no treatment, an aging-elicited group (AE group) consisting of 50-week-old ICR male mice that had undergone no treatment, and a Mixed herbal extract treatment group (MT group) consisting of 50-week-old ICR male mice that had undergone the mixture extract of Fructus amomi Amari, Eucommiae cortex, Bombyx batryticatus treatment (0.1 g/kg/day) for 6 months. After the experiment, the mice from all the experimental groups were dissected, and they were analyzed through histochemical and immunohistochemical methods. The mixture extract of Fructus amomi Amari, Eucommiae cortex, Bombyx batryticatus reduces aging-induced cell damage and oxidative stress and increases the secretion of serotonin and B-endorphin in aged mice, and promotes spermatogenesis in seminiferous tubules and reduces apoptosis and oxidative stress, and increases androgen receptor, $17{\beta}-HSD$ and GnRH, increases the ratio of smooth muscle to collagen fibers in the corpus cavernosum, increases eNOS, decreases PDE-5 and oxidative stress in aged mice, so it improves depression, reproductive, sexual problems caused by Late-onset hypogonadism. the mixture extract of Fructus amomi Amari, Eucommiae cortex, Bombyx batryticatus inhibits the induction of osteoporosis by increasing decreased bone matrix distribution due to aging, increasing the activities of OPC and OPN, which are produced in osteoblasts, and decreasing RANKL, MMP-3 activity, increasing OPG activity. It also reduces muscle damage, oxidative stress, inflammation and apoptosis of muscle tissue, and increases Myo-D in the sartorius muscle of aged mice for improving muscle atrophy caused by by Late-onset hypogonadism.