• Smart Structures and Systems
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• v.24 no.4
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• pp.435-446
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• 2019

The existing piezoelectric spherical transducers with fixed prescribed dynamic characteristics limit their application in scenarios with multi-frequency or frequency variation requirement. To address this issue, this work proposes an improved design of piezoelectric spherical transducers using the resistance tuning method. Two piezoceramic shells are the functional elements with one for actuation and the other for tuning through the variation of load resistance. The theoretical model of the proposed design is given based on our previous work. The effects of the resistance, the middle surface radius and the thickness of the epoxy adhesive layer on the dynamic characteristics of the transducer are explored by numerical analysis. The numerical results show that the multi-frequency characteristics of the transducer can be obtained by tuning the resistance, and its electromechanical coupling coefficient can be optimized by a matching resistance. The proposed design and derived theoretical solution are validated by comparing with the literature given special examples as well as an experimental study. The present study demonstrates the feasibility of using the proposed design to realize the multi-frequency characteristics, which is helpful to improve the performance of piezoelectric spherical transducers used in underwater acoustic detection, hydrophones, and the spherical smart aggregate (SSA) used in civil structural health monitoring, enhancing their operation at the multiple working frequencies to meet different application requirements.

• Ecology and Resilient Infrastructure
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• v.7 no.3
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• pp.189-198
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• 2020

Wetlands, which provide various ecological services, have been regarded as an important nature-based solution for, for example, sustainable water quality improvement and buffering of impacts from climate change. Although the importance of conserving wetlands to reduce the impacts of various perturbations (e.g., changes of land use, climate, and hydrology) has been acknowledged, the possibility of applying these efforts as a nature-based solution in a macro-scale (e.g., landscape) has been insufficient. In this study, we examine the possibility of ecological network analysis that provides an engineering solution as a nature-based solution. Specifically, we analyzed how land use change affects the structural and functional characteristics (connectivity, network efficiency, and clustering coefficient) of the ecological networks by using the ecological networks generated by multiple dispersal models of the hypothetical inhabiting species in wetlandscape. Changes in ecological network characteristics were analyzed through simultaneously removing wetlands, with two initial conditions for surface area, in the zones where land use change occurs. We set a total number of four zones of land use change with different wetland densities. All analyses showed that mean degree and network efficiency were significantly reduced when wetlands in the zones with high wetland density were removed, and this phenomenon was intensified especially when zones contained hubs (nodes with high degree). On the other hand, we observed the clustering coefficient to increase. We suggest our approach for assessing the impacts of land use change on ecological networks, and with additional analysis on betweenness centrality, we expect it can provide a nature-based engineering solution for creating alternative wetlands.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.6
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• pp.36-46
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• 2016

Separate transportation card readers that record the amount of transfer volume occurring during movement in-between lines within the metropolitan railway transfer stations do not exist. This research proposes a model to estimate passenger transit movements in transfer stations that adequately reproduces characteristics arising during a transfer trip. The model used in this study assumes that passengers adopt transfer behaviors that minimize their generalized costs during transfer trips. Further, two measures are sought in order to reflect attributes of the metropolitan railway. The first is that similar paths connect origin and destination stations. For this, the M-Similar Paths method is applied to the model to identify the similar paths that arise. The second is that passengers perceive increasing number of transfers as additional transfer costs, which is reflected by means of the Stepwise Transfer Coefficient. Two case studies of metropolitan railway are used to propose measures for analysis of transfer trips. Twenty directional transit phenomena are reproduced for Sindorim railway station. Aggregate directional transit(A), aggregate inter-line transit(B), and B/A are calculated on a percentage basis for 33 metropolitan railway transfer stations, and using this, the functional role of transfers is explored.

• Journal of Korea Water Resources Association
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• v.48 no.10
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• pp.793-806
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• 2015

The simulation of natural streamflow at ungauged basins is one of the fundamental challenges in hydrology community. The key to runoff simulation in ungauged basins is generally involved with a reliable parameter estimation in a rainfall-runoff model. However, the parameter estimation of the rainfall-runoff model is a complex issue due to an insufficient hydrologic data. This study aims to regionalize the parameters of a continuous rainfall-runoff model in conjunction with a Bayesian statistical technique to consider uncertainty more precisely associated with the parameters. First, this study employed Bayesian Markov Chain Monte Carlo scheme for the estimation of the Sacramento rainfall-runoff model. The Sacramento model is calibrated against observed daily runoff data, and finally, the posterior density function of the parameters is derived. Second, we applied a multiple linear regression model to the set of the parameters with watershed characteristics, to obtain a functional relationship between pairs of variables. The proposed model was also validated with gauged watersheds in accordance with the efficiency criteria such as the Nash-Sutcliffe efficiency, index of agreement and the coefficient of correlation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.3
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• pp.466-472
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• 2008

The paper concerns Fuzzy C-Means clustering based fuzzy neural networks (FCM-FNN) and the optimization of the network is carried out by means of hierarchal fair competition-based parallel genetic algorithm (HFCPGA). FCM-FNN is the extended architecture of Radial Basis Function Neural Network (RBFNN). FCM algorithm is used to determine centers and widths of RBFs. In the proposed network, the membership functions of the premise part of fuzzy rules do not assume any explicit functional forms such as Gaussian, ellipsoidal, triangular, etc., so its resulting fitness values directly rely on the computation of the relevant distance between data points by means of FCM. Also, as the consequent part of fuzzy rules extracted by the FCM-FNN model, the order of four types of polynomials can be considered such as constant, linear, quadratic and modified quadratic. Since the performance of FCM-FNN is affected by some parameters of FCM-FNN such as a specific subset of input variables, fuzzification coefficient of FCM, the number of rules and the order of polynomials of consequent part of fuzzy rule, we need the structural as well as parametric optimization of the network. In this study, the HFCPGA which is a kind of multipopulation-based parallel genetic algorithms(PGA) is exploited to carry out the structural optimization of FCM-FNN. Moreover the HFCPGA is taken into consideration to avoid a premature convergence related to the optimization problems. The proposed model is demonstrated with the use of two representative numerical examples.

• Advances in environmental research
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• v.5 no.3
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• pp.189-200
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• 2016

This study aimed at advanced oxidation of hetero tri-functional reactive dye Acid orange 7 using photo-Fenton conditions in a lab-scale experiment. Decolourisation of Acid Orange 7 dye by Fenton's process was dependent on concentration of Hydrogen peroxide, Ferrous sulphate, pH, and contact time. A $2^3$ factorial design was used to evaluate the effects of these key factors: pH, Fe(II), and $H_2O_2$ concentration, for a dye concentration of 50 mg/L with COD of 340 mg/L at pH 3.0. The response function was removal of colour under optimised conditions; pH 3.0, [Fe(II)] 40.83 mg/L, [$H_2O_2$] 4.97 mmol/L; 13.6 min. of treatment resulting in 100% colour removal. The final COD of treated wastewater was nil suggesting that AOP is a potentially useful process of color removal and dye degradation/mineralisation of effluent having AO7. Minimum contact time for complete decolourisation was at 5 mmol/l $H_2O_2$ concentration. Increase in $FeSO_4$ (mg/l) concentration resulted in decrease of time for complete decolourisation. Box-Behnken Design was used to optimize the process variables. Maximum and minimum levels of pH (3-5), $H_2O_2$ (4-6 mmol/l), $FeSO_4$ (30-46 mg/l) and contact time (5-15 minutes) were used. The statistical analysis revealed a value of 0.88 for coefficient of regression ($R^2$) indicating a good fit of model. Calculated F-value was found higher than the tabulated value confirming to significance of the model. Based on student's t-test, Ferrous sulphate, pH, and contact time have a positive effect on the percent decolourisation of Acid Orange 7.

• Journal of radiological science and technology
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• v.45 no.2
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• pp.151-158
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• 2022

The Cardiac Gated Blood Pool (GBP) scintigram, a nuclear medicine imaging, calculates the left ventricular Ejection Fraction (EF) by segmenting the left ventricle from the heart. However, in order to accurately segment the substructure of the heart, specialized knowledge of cardiac anatomy is required, and depending on the expert's processing, there may be a problem in which the left ventricular EF is calculated differently. In this study, using the DeepLabV3 architecture, GBP images were trained on 93 training data with a ResNet-50 backbone. Afterwards, the trained model was applied to 23 separate test sets of GBP to evaluate the reproducibility of the region of interest and left ventricular EF. Pixel accuracy, dice coefficient, and IoU for the region of interest were 99.32±0.20, 94.65±1.45, 89.89±2.62(%) at the diastolic phase, and 99.26±0.34, 90.16±4.19, and 82.33±6.69(%) at the systolic phase, respectively. Left ventricular EF was calculated to be an average of 60.37±7.32% in the ROI set by humans and 58.68±7.22% in the ROI set by the deep learning segmentation model. (p<0.05) The automated segmentation method using deep learning presented in this study similarly predicts the average human-set ROI and left ventricular EF when a random GBP image is an input. If the automatic segmentation method is developed and applied to the functional examination method that needs to set ROI in the field of cardiac scintigram in nuclear medicine in the future, it is expected to greatly contribute to improving the efficiency and accuracy of processing and analysis by nuclear medicine specialists.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.1
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• pp.1-9
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• 2011

The objective of this paper is to improve the accuracy of the 3D geopositioning extracted from Rational Polynomial Coefficient(RPC) provide in the KOMPSAT-2 metadata files. In this paper, we developed the algorithm to adjust a RFM(Rational Functional Model), and could improve the accuracy of a RFM with this algorithm. Furthermore, when a RFM was adjusted with this algorithm, the effects of the number of GCPs on the accuracy of the adjusted RFM was tested. For accuracy assessment using adjusted RFM, 9 ground control points(GCPs) and 24 check points could be used. Results indicated that the root mean squared errors(RMSEs) of horizontal residual errors calculated 24 check points were 2.20(m). The achieved accuracy of three dimensional object-point determination was 1.72(m) in the X-dimension and 1.37(m) in the Y-dimension and 2.20(m) in the Z-dimension.

• Journal of the Korean Society of Food Science and Nutrition
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• v.25 no.4
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• pp.608-616
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• 1996

To propose the use of skipjack processing by-product(SPB) as a food material, the optimal condition for the production of the SPB hydrolysate through enzyme treatment was obtained using RSM(Response Surface Methodology). Among eight pretenses test, Pretense $P^{TM}$ was screened primarily on the aspect of production cost and taste of the product. The extent of autolysis accompanied by endogenous enzyme in the SPB was almost negligible as compared with that of Protense $P^{TM}$ treatment. The derived model equation was within the satisfiable range as indicated by coefficient of $determination(R^2=0.9460)$ and lack of fit(p>0.1) values. From the results of RSM and ridge analysis, the conditions favoring the higllest degree of hydrolysis were: PH 7.2, $51^{\circ}C,$ reaction time of 3.94 hr, substrate concentration of 33.3%, and enzym $e_strate ratio of 0.48%.48%.8%.

• International Journal of Highway Engineering
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• v.13 no.1
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• pp.239-249
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• 2011

The behavior of the fiber reinforced concrete (FRC) base under environmental loads was analyzed numerically as a fundamental study to develop a high structural and functional performance composite pavement system in which the base was formed using FRC and the asphalt or cement concrete surface was placed on it. A two-dimensional finite element model of the FRC base was developed and the sensitivity study was performed with the variables including slab thickness of base, thermal expansion coefficient, elastic modulus, and tensile and compressive strengths. The crack spacing and crack width were selected as representatives of the base behavior. The effects of the selected variables on the crack spacing and crack width were analyzed and the sensitive variables were determined. The results of this study could be useful to determine the optimal material properties of the FRC base for combining well with the surface materials.