• Journal of Korean Society of Steel Construction
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• v.17 no.5 s.78
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• pp.549-559
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• 2005

A railway bridge with a double composite section is proposed to enhance the structural performance of existing two-girder bridges because the governing design parameter of railway bridges is the flexural stiffness. The concrete deck in negative moment regions is neglected in the design of continuous composite bridges assuming the concrete slab has no resistance to tension. Therefore, the flexural stiffness of the composite section in the negative moment region is reduced resulting in the increase of the depth of the steel section. In order to resolve this disadvantage, several methods are suggested and the double composite section is one of the excellent solutions for extending the span length and increasing the flexural stiffness. In this study, push-out tests on lying studs and mixed stud shear connection with lying and vertical studs were performed to investigate the behavior of the shear connection in the double composite section. Static strength of the shear connection was evaluated through the test results and numerical analyses.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.12
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• pp.523-530
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• 2014

Ontology alignment is the way to share and reuse of ontology knowledge. Because of the ambiguity of concept, most ontology alignment systems combine a set of various measures and complete enumeration to provide the satisfactory result. However, calculating process becomes more complex and required time increases exponentially since the number of concept increases, more errors can appear at the same time. Lately the focus is on meta-matching using the heuristic algorithm. Existing meta-matching system tune extra parameter and it causes complex calculating, as a consequence, the results in the various data of specific domain are not good performed. In this paper, we propose a high performance algorithm by using DCS that can solve ontology alignment through simple process. It provides an efficient search strategy according to distribution of Levy Flight. In order to evaluate the approach, benchmark data from the OAEI 2012 is employed. Through the comparison of the quality of the alignments which uses DCS with state of the art ontology matching systems.

• The Journal of the Acoustical Society of Korea
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• v.19 no.8
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• pp.68-77
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• 2000

Line special frequency (LSF) parameters have been widely used in low bit-rate speech coding due to their efficiency for representing the short-time speech spectrum. In this paper, a new distance measure based on the masking properties of human ear is proposed for quantizing LSF parameters whereas most conventional quantization methods are based on the weighted Euclidean distance measure. The proposed method derives the perceptual distance measure from the definition of noise-to-mask ratio (NMR) which has high correspondence with the actual distortion received in the human ear and uses it for quantizing LSF parameters. In addition, we propose an adaptive bit allocation scheme, which allocates minimal bits to LSF parameters maintaining the perceptual transparency of given speech frame for reducing the average bit-rates. For the performance evaluation, we has shown the ratio of perceptually transparent frames and the corresponding average bit-rates for the conventional and proposed methods. By jointly combining the proposed distance measure and adaptive bit allocation scheme, the proposed system requires only 770 bps for obtaining 95.5% perceptually transparent frames, while the conventional systems produce 89.9% at even 1800 bps.

• Computers and Concrete
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• v.21 no.4
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• pp.407-417
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• 2018

Concrete which is a composite material is one of the most important construction materials. Compressive strength is a commonly used parameter for the assessment of concrete quality. Accurate prediction of concrete compressive strength is an important issue. In this study, we utilized an experimental procedure for the assessment of concrete quality. Firstly, the concrete mix was prepared according to C 20 type concrete, and slump of fresh concrete was about 20 cm. After the placement of fresh concrete to formworks, compaction was achieved using a vibrating screed. After 28 day period, a total of 100 core samples having 75 mm diameter were extracted. On the core samples pulse velocity determination tests and compressive strength tests were performed. Besides, Windsor probe penetration tests and Schmidt hammer tests were also performed. After setting up the data set, twelve artificial intelligence (AI) models compared for predicting the concrete compressive strength. These models can be divided into three categories (i) Functions (i.e., Linear Regression, Simple Linear Regression, Multilayer Perceptron, Support Vector Regression), (ii) Lazy-Learning Algorithms (i.e., IBk Linear NN Search, KStar, Locally Weighted Learning) (iii) Tree-Based Learning Algorithms (i.e., Decision Stump, Model Trees Regression, Random Forest, Random Tree, Reduced Error Pruning Tree). Four evaluation processes, four validation implements (i.e., 10-fold cross validation, 5-fold cross validation, 10% split sample validation & 20% split sample validation) are used to examine the performance of predictive models. This study shows that machine learning regression techniques are promising tools for predicting compressive strength of concrete.

• Earthquakes and Structures
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• v.27 no.4
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• pp.331-344
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• 2024

The performance of reinforced concrete buildings subjected to earthquake excitations depends on the structural behaviour of the superstructure as well as the type of foundation and the properties of soil on which the structure is founded. The consideration of the effects due to the interaction between the structure and soil- foundation alters the seismic response of reinforced concrete buildings subjected to earthquake motion. Evaluation of the structural response of buildings for quantitative assessment of the seismic fragility has been a demanding problem for the engineers. Present research deals with development of fragility curve for building specific vulnerability assessment based on different damage parameters considering the effect of soil-structure interaction. Incremental Dynamic Analysis of fixed base and flexible base RC building models founded on different soil conditions was conducted using finite element software. Three sets of fragility curves were developed with maximum roof displacement, inter storey drift and plastic energy dissipated as engineering demand parameters. The results indicated an increase in the likelihood of exceeding various damage limits by 10-40% for flexible base condition with soft soil profiles. Fragility curve based on energy dissipated showed a higher probability of exceedance for collapse prevention damage limit whereas for lower damage states, conventional methods showed higher probability of exceedance. With plastic energy dissipated as engineering demand parameter, it is possible to track down the intensity of earthquake at which the plastic deformation starts, thereby providing an accurate vulnerability assessment of the structure. Fragility modification factors that enable the transformation of existing fragility curves to account for Soil-Structure Interaction effects based on different damage measures are proposed for different soil conditions to facilitate a congenial vulnerability assessment for buildings with flexible base conditions.

• Investigative Magnetic Resonance Imaging
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• v.21 no.1
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• pp.9-19
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• 2017

Background: Normalized cerebral blood volume (nCBV) can be measured using manual or semiautomatic segmentation method. However, the difference in diagnostic performance on brain tumor differentiation between differently measured nCBV has not been evaluated. Purpose: To compare the diagnostic performance of manually obtained nCBV to that of semiautomatically obtained nCBV on glioblastoma (GBM) and primary central nervous system lymphoma (PCNSL) differentiation. Materials and Methods: Histopathologically confirmed forty GBM and eleven PCNSL patients underwent 3T MR imaging with dynamic susceptibility contrast-enhanced perfusion MR imaging before any treatment or biopsy. Based on the contrast-enhanced T1-weighted imaging, the mean nCBV (mCBV) was measured using the manual method (manual mCBV), random regions of interest (ROIs) placement by the observer, or the semiautomatic segmentation method (semiautomatic mCBV). The volume of enhancing portion of the tumor was also measured during semiautomatic segmentation process. T-test, ROC curve analysis, Fisher's exact test and multivariate regression analysis were performed to compare the value and evaluate the diagnostic performance of each parameter. Results: GBM showed a higher enhancing volume (P = 0.0307), a higher manual mCBV (P = 0.018) and a higher semiautomatic mCBV (P = 0.0111) than that of the PCNSL. Semiautomatic mCBV had the highest value (0.815) for the area under the curve (AUC), however, the AUCs of the three parameters were not significantly different from each other. The semiautomatic mCBV was the best independent predictor for the GBM and PCNSL differential diagnosis according to the stepwise multiple regression analysis. Conclusion: We found that the semiautomatic mCBV could be a better predictor than the manual mCBV for the GBM and PCNSL differentiation. We believe that the semiautomatic segmentation method can contribute to the advancement of perfusion based brain tumor evaluation.

• Journal of Energy Engineering
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• v.25 no.1
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• pp.69-75
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• 2016

Bubble size is a key parameter for an accurate prediction of bubble behaviours in the multi-dimensional two-phase flow. In the current STAR CCM+ CFD code, a mechanistic bubble size model $S{\gamma}$ is available for the prediction of bubble size in the flow channel. As another model, Yun model is developed based on DEBORA that is subcooled boiling data in high pressure. In this study, numerical simulation for the gas-liquid two-phase flow was conducted to validate and confirm the performance of $S{\gamma}$ model and Yun model, using the commercial CFD code STAR CCM+ ver. 10.02. For this, local bubble models was evaluated against the air-water data from DEDALE experiments (1995) and Hibiki et al. (2001) in the vertical pipe. All numerical results of $S{\gamma}$ model predicted reasonably the two-phase flow parameters and Yun model is needed to be improved for the prediction of air-water flow under low pressure condition.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.8
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• pp.2157-2163
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• 2009

The oxygen permeability of a soft contact lens is an important parameter for determining corneal health when considering the physiological response of the eye. The aim of this study is to evaluate the oxygen permeability of soft contact lenses based on thickness, using the polarographic method. The thickness of lens was measured using contact and non-contact method. To assess accuracy and reliability, the Bland-Altman plot was used. The reliability was high for the oxygen permeability based on center thickness measured by contact method, whereas the accuracy was high for the oxygen permeability based on center thickness measured by non-contact method. These results indicate that the permeability characteristics were variable according to the measurement and criteria of thickness of soft contact lenses and the measurement of soft contact lenses by non-contact method was more reasonable. Thus, contact lens practitioners should consider some basic differences between methodologies when interpreting or quoting oxygen performance data.

• Journal of the Korean GEO-environmental Society
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• v.23 no.6
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• pp.5-17
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• 2022

The performance of the relief wells installed for the purpose of controlling seepage of the dam embankment is affected by various parameters such as diameter, spacing, penetration rate, permeability coefficient of the ground, thickness of the foundation layer. Therefore, when the relief wells are adopted for the purpose of reducing seepage pressure, these parameters should be sufficiently reviewed to determine the installation specifications of the relief wells. This study evaluated the effect of the length of the geosynthetics blanket on the performance of the relief wells installed in the downstream part of the dam embankment with blankets in the upstream and downstream part of the dam embankment as countermeasure methods to control seepage of the dam embankment. In the relationship between the length of the upstream and downstream blanket and the discharge, the discharge of the relief wells decreases as the length of the upstream blanket increases, and on the other hand, the discharge of the relief wells decreases as the length of the downstream blanket increases. In the upper and lower blanket length-spacing relationship, as the length of the upstream blanket increases, the spacing of the relief wells increases and as the length of the downstream blanket increases, the spacing of the relief wells decreases. Therefore, when installing the relief wells in parallel with the blanket, it was found that increasing the length of the upstream blanket is more efficient than increasing the length of the downstream blanket in order to minimize the discharge of seepage discharge and to ensure economic feasibility by wider installation of the relief wells.

• Journal of Energy Engineering
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• v.29 no.2
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• pp.1-9
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• 2020

In recent days, fuel cell has received attention from the world as an alternative power source to hydrocarbon used in automobile engines. With the industrial advances of fuel cell, There have been a lot of researches actively conducted to find a way of generating hydrogen. Among many hydrogen production methods, Solid Oxide Electrolysis Cell(SOEC) is not only a basic way but also environment-friendly method to produce hydrogen gas. Solid Oxide Electrolysis Cell has lower electrical energy demands and high thermal efficiency since it is possible to operate under high temperature and high pressure conditions. For these reasons, experimental researches as well as studies on numerical modeling for Solid Oxide Electrolysis Cell have been under way. However, studies on numerical modeling are relatively less enough than experimental accomplishments and have limited performance prediction, which mostly is considered as a result from inadequate effects of electrochemical properties by temperature and pressure. In this study, various experimental studies of commercial Membrane Electrode Assembly (MEA) composed of Ni-YSZ (40wt%, Ni-60 wt% YSZ)/8-YSZ (TOSOH, TZ8Y)/LSM (La_0.9Sr_0.1MnO₃) was utilized for improving effectiveness of SOEC model. After numerically analyzing effects of electrochemical properties according to operating temperature, causing the largest deviation between experiments and simulation are that Charge Transfer Coefficient (CTC), exchange current density, diffusion coefficient, electrical conductivity in SOEC. Analyzing temperature effect on parameter used in overpotential model is conducted for modeling of SOEC. cross-validation method is adopted for application of various MEA and evaluating feasibility of model. As a result, the study confirm that the numerical model of SOEC based on structured process of effectiveness evaluation makes performance prediction better.