• Environmental Engineering Research
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• v.19 no.2
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• pp.157-163
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• 2014

The adsorption of Cr(VI) from aqueous solutions to activated carbon fiber (ACF) was investigated using both batch and flow-through column experiments. The batch experiments (adsorbent dose, 10 g/L; initial Cr(VI) concentration, 5-500 mg/L) showed that the maximum adsorption capacity of Cr(VI) to ACF was determined to 20.54 mg/g. The adsorption of Cr(VI) to ACF was sensitive to solution pH, decreasing from 9.09 to 0.66 mg/g with increasing pH from 2.6 to 9.9; the adsorption capacity was the highest at the highly acidic solution pHs. Kinetic model analysis showed that the Elovich model was the most suitable for describing the kinetic data among three (pseudo-first-order, pseudo-second-order, and Elovich) models. From the nonlinear regression analysis, the Elovich model parameter values were determined to be ${\alpha}$ = 162.65 mg/g/h and ${\beta}$ = 2.10 g/mg. Equilibrium isotherm model analysis demonstrated that among three (Langmuir, Freundlich, Redlich-Peterson) models, both Freundlich and Redlich-Peterson models were suitable for describing the equilibrium data. In the model analysis, the Redlich-Peterson model fit was superimposed on the Freundlich fit. The Freundlich model parameter values were determined to be $K_F$ = 0.52 L/g and 1/n = 0.56. The flow-through column experiments showed that the adsorption capacities of ACF in the given experimental conditions (column length, 10 cm; inner diameter, 1.5 cm; flow rate, 0.5 and 1.0 mL/min; influent Cr(VI) concentration, 10 mg/L) were in the range of 2.35-4.20 mg/g. This study demonstrated that activated carbon fiber was effective for the removal of Cr(VI) from aqueous solutions.

• Korean Journal of Environmental Agriculture
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• v.30 no.4
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• pp.357-366
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• 2011

BACKGROUND: Mathematical model such as GLEAMS have been developed and successfully applied to upland fields to estimate the level of pesticide residues in soil. But, the GLEAMS model rarely applied to the Korean conditions. METHODS AND RESULTS: To evaluate pesticide transport in soil residue using the GLEAMS model from pepper plot, Alachlor, Endosulfan, Cypermethrin and Fenvalerate were applied for standard and double rate. Soil sampling was conducted and decaying patterns of pesticides were investigated. Observed climate data such as temperature and irrigation amount were used for hydrology simulation. The observed pesticide residue data of 2008 were used for parameter calibration, and validation of GLEAMS model was conducted with observed data of 2009. After calibration, the $K_{oc}$ (Organic carbon distribution coefficient) and WSHFRC (Washoff fraction) parameters were identified as key parameters. The simulated concentrations of the pesticides except Fenvalerate were sensitive to $K_{oc}$ parameter. Overall, soil residue concentrations of Alachlor, Cypermethrin and Fenvalerate were fairly simulated compared to those of Endosulfan. The applicability of the GLEAMS model was also confirmed by statistical analysis. CONCLUSION(s): GLEAMS model was eligible for evaluation of pesticide soil residue for Alachlor, Cypermethrin and Fenvalerate.

• Korean Management Science Review
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• v.32 no.1
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• pp.1-13
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• 2015

We estimate the option value embedded in reverse mortgages using the framework of European put option. The reverse mortgage is a very useful financial product for senior citizens who own homes but do not have a cash income while it is a high risk one from lender's perspective. One of benefits of the reverse mortgages is that the debt limit is restricted to the scope of the disposition price of the collateralized house, which is considered a put option to borrowers. The put option is evaluated using Black-Scholes model and a sensitive analysis is performed on variables such as discount rate, volatility, and time period. We confirm that the option value of reverse mortgages increases rapidly as the borrowers live longer than their life expectancy. The results of this study can be used to promote the reverse mortgage program more effectively in order to solve the problem of income shortage of the elderly homeowners.

• Journal of Distribution Science
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• v.16 no.7
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• pp.35-45
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• 2018

Purpose - The study investigates the impact of consignment on the economic performance in the supply chain with three stages. Through the analysis on distinct forms of consignment application, this study intends to answer to the question of how the consignment should be used in the multi-stage supply chain. Research design, data, and methodology - The proposed mathematical model represents the supply chain system with a manufacturer, a wholesaler, and a retailer. Three different forms of consignment application are considered depending on which stages adapt the consignment, and their system profits are compared with the traditional non-consignment system in numerical examples. Results - The numerical examples show that the serial consignment application performs better than any other forms of consignment as well as the non-consignment system. The additional analysis indicates that the system profit is significantly sensitive to the consignment rate. Conclusions - The outcome of this study implies the potential of consignment to improve the system performance even in the multi-stage supply chain system. Meanwhile, each supply chain member's preference to the specific form of consignment application could be different depending on which stage he has. All the supply chain members should jointly determine the appropriate consignment rates to obtain the best system performance.

• Smart Media Journal
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• v.1 no.4
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• pp.18-26
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• 2012

The increase of the number of smartphone applications has enforced the importance of new user interface emergence and has raised the interest of research in the convergence of multiple sensors. In this paper, we propose a method for the convergence of acceleration, magnetic and gyro sensors to recognize the gesture from motion of user smartphone. The proposed method first obtain the 3D orientation of smartphone and recognize the gesture of hand motion by using HMM(Hidden Markov Model). The proposed method for the representation for 3D orientation of smartphone in spherical coordinate was used for quantization of smartphone orientation to be more sensitive in rotation axis. The experimental result shows that the success rate of our method is 93%.

• Journal of Environmental Science International
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• v.26 no.10
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• pp.1135-1146
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• 2017

At riverbank filtration sites, groundwater levels of alluvial aquifers near rivers are sensitive to variation in river discharge and pumping quantities. In this study, the groundwater level fluctuation, pumping quantity, and streamflow rate at the site of a riverbank filtration plant, which produces drinking water, in the lower Nakdong River basin, South Korea were interrelated. The relationship between drawdown ratio and river discharge was very strong with a correlation coefficient of 0.96, showing a greater drawdown ratio in the wet season than in the dry season. Autocorrelation and cross-correlation were carried out to characterize groundwater level fluctuation. Autoregressive model analysis of groundwater water level fluctuation led to efficient estimation and prediction of pumping for riverbank filtration in relation to river discharge rates, using simple inputs of river discharge and pumping data, without the need for numerical models that require data regarding several aquifer properties and hydrologic parameters.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.19 no.1
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• pp.86-93
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• 2007

The PEM (polymer electrolyte membrane) fuel cell is one of the promising fuel cell systems as a new small power generating device for automobiles and buildings. The optimal design of cooling plates installed between MEA (membrane electrode assembly) is very important to achieve high performance and reliability of the PEMFC because it is very sensitive to temperature variations. In this study, six types of cooling plate models for the PEMFC including basic serpentine and parallel shapes were designed and their cooling performances were analyzed by using three-dimensional fluid dynamics with commercial software. The model 3 designed by revising the basic serpentine model represented the best cooling performance among them in the aspect of uniformity of temperature distribution and thermal reliability, The serpentine models showed higher pressure drop than the parallel models due to a higher flow rate.

• Smart Structures and Systems
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• v.26 no.4
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• pp.451-468
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• 2020

Although model updating has been widely applied using a specific optimization algorithm with a single objective function using frequencies, mode shapes or frequency response functions, there are few studies that investigate hybrid optimization algorithms for real structures. Many of them did not take into account the sensitivity of the updating parameters to the model outputs. Therefore, in this paper, optimization algorithms and sensitivity analysis are applied for model updating of a real cable-stayed bridge, i.e., the Kien bridge in Vietnam, based on experimental data. First, a global sensitivity analysis using Morris method is employed to find out the most sensitive parameters among twenty surveyed parameters based on the outputs of a Finite Element (FE) model. Then, an objective function related to the differences between frequencies, and mode shapes by means of MAC, COMAC and eCOMAC indices, is introduced. Three metaheuristic algorithms, namely Gravitational Search Algorithm (GSA), Particle Swarm Optimization algorithm (PSO) and hybrid PSOGSA algorithm, are applied to minimize the difference between simulation and experimental results. A laboratory pipe and Kien bridge are used to validate the proposed approach. Efficiency and reliability of the proposed algorithms are investigated by comparing their convergence rate, computational time, errors in frequencies and mode shapes with experimental data. From the results, PSO and PSOGSA show good performance and are suitable for complex and time-consuming analysis such as model updating of a real cable-stayed bridge. Meanwhile, GSA shows a slow convergence for the same number of population and iterations as PSO and PSOGSA.

• Journal of Ocean Engineering and Technology
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• v.28 no.6
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• pp.552-559
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• 2014

In general, the number of underwater transient signals is very limited for research on automatic recognition. Data-dependent feature extraction is one of the most effective methods in this case. Therefore, we suggest WPCC (Wavelet packet ceptsral coefficient) as a feature extraction method. A wavelet packet best tree for each data set is formed using an entropy-based cost function. Then, every terminal node of the best trees is counted to build a common wavelet best tree. It corresponds to flexible and non-uniform filter bank reflecting characteristics for the data set. A GMM (Gaussian mixture model) is used to classify five classes of underwater transient data sets. The error rate of the WPCC is compared using MFCC (Mel-frequency ceptsral coefficients). The error rates of WPCC-db20, db40, and MFCC are 0.4%, 0%, and 0.4%, respectively, when the training data consist of six out of the nine pieces of data in each class. However, WPCC-db20 and db40 show rates of 2.98% and 1.20%, respectively, while MFCC shows a rate of 7.14% when the training data consists of only three pieces. This shows that WPCC is less sensitive to the number of training data pieces than MFCC. Thus, it could be a more appropriate method for underwater transient recognition. These results may be helpful to develop an automatic recognition system for an underwater transient signal.

• Environmental Engineering Research
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• v.20 no.3
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• pp.223-229
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• 2015

The application of coagulation for feed water pretreatment prior to microfiltration (MF) process has been widely adopted to alleviate fouling due to particles and organic matters in feed water. However, the efficiency of coagulation pretreatment for MF is sensitive to its operation conditions such as pH and coagulant dose. Moreover, the optimum coagulation condition for MF process is different from that for rapid sand filtration in conventional drinking water treatment. In this study, the use of response surface methodology (RSM) was attempted to determine coagulation conditions optimized for pretreatment of MF. The center-united experimental design was used to quantify the effects of coagulant dose and pH on the control of fouling control as well as the removal organic matters. A MF membrane (SDI Samsung, Korea) made of polyvinylidene fluoride (PVDF) was used for the filtration experiments. Poly aluminum chloride (PAC) was used as the coagulant and a series of jar tests were conducted under various conditions. The flux was $90L/m^2-h$ and the fouling rate were calculated in each condition. As a result of this study, an empirical model was derived to explore the optimized conditions for coagulant dose and pH for minimization of the fouling rate. This model also allowed the prediction of the efficiency of the coagulation efficiency. The experimental results were in good agreement with the predictions, suggesting that RSM has potential as a practical method for modeling the coagulation pretreatment for MF.