• Steel and Composite Structures
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• v.25 no.6
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• pp.671-684
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• 2017

Elastic-plastic shear buckling behaviors of the web-post in a Castellated Steel Beam (CSB) with hexagonal web openings under vertical shear force were investigated further using Finite Element Model (FEM) based on a sub-model, which took the upper part of the web-post under horizontal shear force to represent the whole web-post under vertical shear force. A simplified design method for the web-post elastic-plastic shear buckling strength was proposed based on simulation results of the sub-model. Proper boundary conditions were applied to the sub-model to assure that its behaviors were identical to those of the whole web-post. The equation to calculate the thin plate elastic shear buckling strength was adopted as the basic form to build the design equation for elastic-plastic buckling strength of the sub-model. Parameters that might affect the elastic-plastic shear buckling strength of the whole web-post were studied. After obtaining the vertical shear buckling strength of a sub-model through FEM, the shear buckling coefficient k can be obtained through the back analysis. A practical calculation method for k was proposed through curving fitting the parameter study results. The elastic-plastic shear buckling strength of the web-post calculated using the proposed shear buckling coefficient k agreed well with that obtained from the FEM and test results. And it was more precise than those obtained from EC3 based on the strut model.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.221-227
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• 2013

This paper proposes an improved steganalysis method based on image categorization. In general, most steganalysis methods extract the statistical moments based features which contain the global natures of images regardless of their inherent characteristics. However, the steganalysis method based on the statistical moments leads to degraded performance by applying to images with different complexity. In this paper, we decompose an 8-bit image into an upper 4-bit plane and a lower 4-bit plane, and categorize the image with two classes according to the correlation coefficient between decomposed sub-images. Two independent steganalyses can be performed for the categorized images. Since our method uses independent steganalysis technique according to the image category, it can reduce the drawback of the steganalysis methods utilizing the statistical moments. The performance of the proposed scheme is compared with well-known four steganalysis methods. Experiment results show that the proposed scheme has higher detection rate than previous methods.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.193-202
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• 2022

The classification of hyperspectral imagery (HSI) is essential in the surface of earth observation. Due to the continuous large number of bands, HSI data provide rich information about the object of study; however, it suffers from the curse of dimensionality. Dimensionality reduction is an essential aspect of Machine learning classification. The algorithms based on feature extraction can overcome the data dimensionality issue, thereby allowing the classifiers to utilize comprehensive models to reduce computational costs. This paper assesses and compares two HSI classification techniques. The first is based on the Joint Spatial-Spectral Stacked Autoencoder (JSSSA) method, the second is based on a shallow Artificial Neural Network (SNN), and the third is used the SVM model. The performance of the JSSSA technique is better than the SNN classification technique based on the overall accuracy and Kappa coefficient values. We observed that the JSSSA based method surpasses the SNN technique with an overall accuracy of 96.13% and Kappa coefficient value of 0.95. SNN also achieved a good accuracy of 92.40% and a Kappa coefficient value of 0.90, and SVM achieved an accuracy of 82.87%. The current study suggests that both JSSSA and SNN based techniques prove to be efficient methods for hyperspectral classification of snow features. This work classified the labeled/ground-truth datasets of snow in multiple classes. The labeled/ground-truth data can be valuable for applying deep neural networks such as CNN, hybrid CNN, RNN for glaciology, and snow-related hazard applications.

• Journal of electromagnetic engineering and science
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• v.14 no.4
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• pp.382-386
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• 2014

The knowledge of substrate material properties is important in antenna design. We present a technique to accurately characterize the dielectric constant and loss tangent of an antenna substrate based on the measurements of antenna's reflection coefficient and bandwidth. In this technique, an error function is formulated by combinations of the reflection coefficient and bandwidth of measured and simulated data, and then an optimization technique is used to efficiently search for the substrate properties that minimize the error function. The results show that the method is effective in retrieving the dielectric constant and loss tangent of the antenna substrate without the need of additional test fixtures as in conventional substrate characterization methods.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.142-149
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• 2013

In general, a color of an image is represented by using red, green, and blue channels in a RGB camera system. However, only information of three channels are limited to estimate a spectral reflectance of a real scene. Because of this, the RGB camera system can not accurately represent the color. To overcome this limitation and represent an accurate color, researches to estimate the spectral reflectance by using a multi-channel camera system are being actively proceeded. Recently, a reflectance estimation method adaptively constructing a similar training set from a traditional training set according to a camera response by using a spectral similarity was introduced. However, in this method, an accuracy of the similar training set is reduced because the spectral similarity based on an average and a maximum distances was applied. In this paper, a reflectance estimation method applied a spectral similarity based on a correlation coefficient is proposed to improve the accuracy of the similar training set. Firstly, the correlation coefficient between the similar training set and the spectral reflectance obtained by Wiener estimation method is calculated. Secondly, the similar training set is constructed from the traditional training set according to the correlation coefficient. Finally, Wiener estimation method applied the similar training set is performed to estimate the spectral reflectance. To evaluate a performance of the proposed method with previous methods, experimental results are compared. As a result, the proposed method showed the best performance.

• Structural Engineering and Mechanics
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• v.66 no.5
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• pp.649-663
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• 2018

The scaled boundary finite element method is extended to evaluate the dynamic stress intensity factors and T-stress with a numerical procedure based on the improved continued-fraction. The improved continued-fraction approach for the dynamic stiffness matrix is introduced to represent the inertial effect at high frequencies, which leads to numerically better conditioned matrices. After separating the singular stress term from other high order terms, the internal displacements can be obtained by numerical integration and no mesh refinement is needed around the crack tip. The condition numbers of coefficient matrix of the improved method are much smaller than that of the original method, which shows that the improved algorithm can obtain well-conditioned coefficient matrices, and the efficiency of the solution process and its stability can be significantly improved. Several numerical examples are presented to demonstrate the increased robustness and efficiency of the proposed method in both homogeneous and bimaterial crack problems.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.26 no.12
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• pp.1707-1714
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• 2002

This paper deals with the development of a new method that can obtain heat transfer coefficient and reference free stream temperature simultaneously, The method is based on transient heat transfer experiments using two narrow-band TLCs. The method is validated through error analysis in terms of the random uncertainties in the measured temperatures. It is found that the errors could be reduced more than 2 times less. The general method described in this paper is applicable to many heat transfer models with unknown free stream temperature.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.213-221
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• 2022

Defects are the risk factors in the construction process of buildings. They cause damage, delaying the construction duration. They especially cause adverse effects on the top-down construction method. This study analyzed the degree of construction delay induced by each work type, focusing on defects in the top-down method. Then, we derived construction delay induction coefficient from different work types in order by using the severity of construction delay per defect and the occurrence probability of defect; this assessment model measures the impact of defects on construction delay for each work type. Furthermore, by comparing each work type based on the defect frequency and the construction delay induction coefficient, we found work types that need to be administered attentively. We identified that plastering work was easy to overlook, requiring caution in defect management. This study provides an efficient defect management system suitable for the buildings that are built using the top-down construction method.

• Smart Structures and Systems
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• v.25 no.2
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• pp.169-181
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• 2020

Sensor placement is a crucial aspect of bridge health monitoring (BHM) dedicated to accurately estimate and locate structural damages. In addressing this goal, a sensor placement framework based on the deflection influence line (DIL) analysis is here proposed, for the optimal design of damage detection-oriented BHM system. In order to improve damage detection accuracy, we explore the change of global stiffness matrix, damage coefficient matrix and DIL vector caused by structural damage, and thus develop a novel sensor placement framework based on the Fisher information matrix. Our approach seeks to determine the contribution of each sensing node to damage detection, and adopts a distance correction coefficient to eliminate the information redundancy among sensors. The proposed damage detection-oriented optimal sensor placement (OSP) method is verified by two examples: (1) a numerically simulated three-span continuous beam, and (2) the Pinghu bridge which has existing real damage conditions. These two examples verify the performance of the distance corrected damage sensitivity of influence line (DSIL) method in significantly higher contribution to damage detection and lower information redundancy, and demonstrate the proposed OSP framework can be potentially employed in BHM practices.

• Journal of Pharmaceutical Investigation
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• v.23 no.3
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• pp.1-8
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• 1993

A simple and quick method based on the transient diffusion theory for predicting the steady state rate of penetration of a drug after transdermal drug administration was proposed. The amount of drug entering the stratum corneum was determined by 20 strippings with an adhesive tape. From the profile of the amount of drug as a function of the number of strippings, the quantity of drug on the surface of stratum corneum was extrapolated. Based on the amounts of drug entering the stratum corneum during two time intervals $(t_1\;and\;t_2)$ within 1 hour after the application, the diffusion and partition coefficient were determined. Once the diffusion coefficient of the drug in the stratum corneum and the partition coefficient (stratum corneum/vehicle) were determined from the present approach, the steady-state flux of penetration across the stratum corneum was calculated. The steady-state rates of penetration of ascorbic acid and estradiol across hairless mouse skin were evaluated from this approach and compared with those obtained from ill vitro penetration experiment using excised hairless mouse skin. The data confirmed that the proposed method can predict the steady-state rate of penetration of these drugs across the stratum corneum.