• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.4
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• pp.2029-2035
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• 2014

In this study, we conducted the adsorption equilibrium and batch experiments of dissolved organic carbon (DOC) in the wastewater by granular activated carbon (GAC). The components of organic compound were Beef extract (1.8 mg/L), Peptone (2.7 mg/L), Humic acid (4.2 mg/L), Tannic acid (4.2 mg/L), Sodium lignin sulfonate (2.4 mg/L), Sodium lauryle sulfate (0.94 mg/L), Arabic gum powder (4.7 mg/L), Arabic acid (polysaccharide) (5.0 mg/L), $(NH_4)_2SO_4$ (7.1 mg/L), $K_2HPO_4$ (7.0 mg/L), $NH_4HCO_3$ (19.8 mg/L), $MgSO_4{\cdot}7H_2O$ (0.71 mg/L), The adsorption characteristics of DOC in synthetic wastewater was described using the mathematical model through a series of isotherm and batch experiments. It showed that there was linear adsorption region in the low DOC concentration (0~2.5 mg/L) and favorable adsorption region in high concentration (2.5~6 mg/L). The synthetic wastewater used was prepared using known quantities of organic and/or inorganic compounds. Adsorption modelling isotherms were predicted by the Freundlich, Langmuir, Sips and hybrid isotherm equations. Especially, hybrid isotherm of Linear and Sips equation was a good adsorption equilibrium in the region of the both the low concentration and high concentration. In applying carbon adsorption for treating water and wastewater, hybrid adsorption equation plus linear equation with Sips equation will be a good new adsorption equilibrium model. Linear driving force approximation (LDFA) kinetic equation with Hybrid (linear+Sips) adsorption isotherm model was successfully applied to predict the adsorption kinetics data in various GAC adsorbent amounts.

• Journal of Nutrition and Health
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• v.51 no.6
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• pp.567-579
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• 2018

Purpose: This study examined the mediation effects of dietary habits, nutrient intake, daily life in the relationship between the working hours of Korean shift workers and metabolic syndrome. Methods: Data were collected from the sixth (2013-2015) Korea National Health and Nutrition Examination Survey (KNHANES). The stochastic regression imputation was used to fill missing data. Statistical analysis was performed in Korean shift workers with metabolic syndrome using the SPSS 24 program for Windows and a structural equation model (SEM) using an analysis of moment structure (AMOS) 21.0 package. Results: The model fitted the data well in terms of the goodness of fit index (GFI) = 0.939, root mean square error of approximation (RMSEA) = 0.025, normed fit index (NFI) = 0.917, Tucker-Lewis index (TLI) = 0.984, comparative fit index (CFI) = 0.987, and adjusted goodness of fit index (AGFI) = 0.915. Specific mediation effect of dietary habits (p = 0.023) was statistically significant in the impact of the working hours of shift workers on nutrient intake, and specific mediation effect of daily life (p = 0.019) was statistically significant in the impact of the working hours of shift workers on metabolic syndrome. On the other hand, the dietary habits, nutrient intake and daily life had no significant multiple mediator effects on the working hours of shift workers with metabolic syndrome. Conclusion: The appropriate model suggests that working hours have direct effect on the daily life, which has the mediation effect on the risk of metabolic syndrome in shift workers.

• Economic and Environmental Geology
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• v.43 no.3
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• pp.259-267
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• 2010

Resistivity logging instruments were designed to measure electrical resistivity of formation, which can be directly interpreted to provide water-saturation profile. Short and long normal logging measurements are made under groundwater level. In some investigation sites, groundwater level reaches to a depth of a few meters. It has come to attention that the proximity of groundwater level might distort short and long normal logging readings, when the measurements are made near groundwater level, owing to the proximity of an insulating air. This study investigates the effects of the proximity of groundwater level (and also the proximity of earth surface) on the normal by simulating normal logging measurements near groundwater level. In the simulation, we consider all the details of real logging situation, i.e., the presence of wellbore, the tool mandrel with current and potential electrodes, and currentreturn and reference-potential electrodes. We also model the air to include the earth’'s surface in the simulation rather than the customary choice of imposing a boundary condition. To obtain apparent resistivity, we compute the voltage, i.e., potential difference between monitoring and reference electrodes. For the simulation, we use a twodimensional, goal-oriented and high-order self-adaptive hp finite element refinement strategy (h denotes the element size and p the polynomial order of approximation within each element) to obtain accurate simulation results. Numerical results indicate that distortion on the normal logging is greater when the reference potential electrode is closer to the borehole and distortions on long normal logging are larger than those on short normal logging.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.620-626
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• 2004

For general nonlinear processes, it is difficult to control with a linear model-based control method and nonlinear controls are considered. Among the numerous approaches suggested, the most rigorous approach is to use dynamic optimization. Many general engineering problems like control, scheduling, planning etc. are expressed by functional optimization problem and most of them can be changed into dynamic programming (DP) problems. However the DP problems are used in just few cases because as the size of the problem grows, the dynamic programming approach is suffered from the burden of calculation which is called as 'curse of dimensionality'. In order to avoid this problem, the Neuro-Dynamic Programming (NDP) approach is proposed by Bertsekas and Tsitsiklis (1996). To get the solution of seriously nonlinear process control, the interest in NDP approach is enlarged and NDP algorithm is applied to diverse areas such as retailing, finance, inventory management, communication networks, etc. and it has been extended to chemical engineering parts. In the NDP approach, we select the optimal control input policy to minimize the value of cost which is calculated by the sum of current stage cost and future stages cost starting from the next state. The cost value is related with a weight square sum of error and input movement. During the calculation of optimal input policy, if the approximate cost function by using simulation data is utilized with Bellman iteration, the burden of calculation can be relieved and the curse of dimensionality problem of DP can be overcome. It is very important issue how to construct the cost-to-go function which has a good approximate performance. The neural network is one of the eager learning methods and it works as a global approximator to cost-to-go function. In this algorithm, the training of neural network is important and difficult part, and it gives significant effect on the performance of control. To avoid the difficulty in neural network training, the lazy learning method like k-nearest neighbor method can be exploited. The training is unnecessary for this method but requires more computation time and greater data storage. The pH neutralization process has long been taken as a representative benchmark problem of nonlin ar chemical process control due to its nonlinearity and time-varying nature. In this study, the NDP algorithm was applied to pH neutralization process. At first, the pH neutralization process control to use NDP algorithm was performed through simulations with various approximators. The global and local approximators are used for NDP calculation. After that, the verification of NDP in real system was made by pH neutralization experiment. The control results by NDP algorithm was compared with those by the PI controller which is traditionally used, in both simulations and experiments. From the comparison of results, the control by NDP algorithm showed faster and better control performance than PI controller. In addition to that, the control by NDP algorithm showed the good results when it applied to the cases with disturbances and multiple set point changes.

• Journal of Korean Society of Transportation
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• v.20 no.1
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• pp.55-63
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• 2002

It has been known well that Traffic Conflict Technique(TCT) used to evaluate the safety of intersections in the case of shortage of traffic accidents data and surveying time. Because data for using in traffic conflict technique that is collected by trained surveyors, it is rely on the knowledge, experience and the characteristics of them. The data of surveying generate varying result. So, its variance must minimize and then it is considered of calculating in traffic conflict technique however obviously technique to minimize has not developed until now. So, this paper has a focus on the technical method to minimize the variance. For this, it applied the fuzzy reasoning theory to the existed traffic conflict technique that is the most comprehensive method in the country and then developed the new traffic conflict technique model. Fuzzy reasoning theory is a very appropriate method for minimizing the variance among surveyors because it can systematically calculate the uncertainty of surveyors by approximation reasoning structure. The result of analysis from pilot study, the new Procedure in this Paper minimized the variance by 53 Percentiles and it increased the value of conversion factor two times than the exited traffic conflict technique. The method proposed in this paper, it can be used for evaluating the safety of intersection, and before and after analysis of improving Project of black spots.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.12
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• pp.1825-1836
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• 2008

Many applications in computer graphics require complex and highly detailed models. However it is often desirable to use approximations in place of excessively detailed models in order to control the processing time. Thus, we aim to develop a notion of optimal matrix to simplify surface which can rapidly obtain the high quality 2D patterns flattening 3D surface as follows. Firstly, two 3D bodies are modeled based on existing Size Korea data. Secondly, each model is divided by shell and block for its pattern draft. Thirdly, each block is flattened by grid and bridge method. Finally, we selected the optimal matrix and demonstrated the efficiency and quality of the proposed method. This proposed approach accommodates surfaces with darts, which are commonly used in the clothing industry to reduce the deformation of surface forming and flattening. The resulting optimal matrix could be an initiation of standardization for pattern flattening. It is expected that this method could facilitate much better approximation in both efficiency and precision.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.5
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• pp.345-352
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• 2014

In this paper, the CAD data for the optimal shape design obtained by isogeometric shape optimization is directly used to fabricate the specimen by using 3D printer for the experimental validation. In a conventional finite element method, the geometric approximation inherent in the mesh leads to the accuracy issue in response analysis and design sensitivity analysis. Furthermore, in the finite element based shape optimization, subsequent communication with CAD description is required in the design optimization process, which results in the loss of optimal design information during the communication. Isogeometric analysis method employs the same NURBS basis functions and control points used in CAD systems, which enables to use exact geometrical properties like normal vector and curvature information in the response analysis and design sensitivity analysis procedure. Also, it vastly simplify the design modification of complex geometries without communicating with the CAD description of geometry during design optimization process. Therefore, the information of optimal design and material volume is exactly reflected to fabricate the specimen for experimental validation. Through the design optimization examples of elasticity problem, it is experimentally shown that the optimal design has higher stiffness than the initial design. Also, the experimental results match very well with the numerical results. Using a non-contact optical 3D deformation measuring system for strain distribution, it is shown that the stress concentration is significantly alleviated in the optimal design compared with the initial design.

• Journal of the Korean Geotechnical Society
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• v.19 no.5
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• pp.133-144
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• 2003

Horizontal consolidation characteristics of Busan marine clay were investigated by computing coefficient of horizontal consolidation from Piezocone data and comparing their results with those of standard consolidation test. It is well known that current prediction models of $c_h$ for high plastic soils have large uncertainties, and show a great difference between the predicted and the measured values. However, the spherical models and expanding cavity theory of Torstensson(1977), and Burns & Mayne(1998) based on modified Cam-Clay model with critical limit state concepts have relative reliability in estimating $c_h$ and good applicability in highly plasticity soils. In this paper, a normalization technique was used to evaluate $c_h$ using the Burns and Mayne's method based on the dissipation test, and their normalized consolidation curves give 0.015 of time factor($T_{50}$) when 50% degree of consolidation is completed. Comparison study using Piezocone data obtained at other similar ground site shows 1.5 times less systematicality than that of standard consolidation test, which indicates considerable approximation with the measured values because standard consolidation test gives the difference of three to few times compared with the measured values. In addition, design chart for estimating $c_h$ based on the chart from Robertson et al.(1992) and using the other method of the direct prediction from the of dissipation test was newly proposed. It is judged that new proposed chart is very applicable to Korean marine soils, especially in very high plastic soils.

• Journal of Communications and Networks
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• v.14 no.4
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• pp.374-384
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• 2012

Utilizing artificial noise (AN) is a good means to guarantee security against eavesdropping in a multi-inputmulti-output system, where the AN is designed to lie in the null space of the legitimate receiver's channel direction information (CDI). However, imperfect CDI will lead to noise leakage at the legitimate receiver and cause significant loss in the achievable secrecy rate. In this paper, we consider a delayed feedback system, and investigate the impact of delayed CDI on security by using a transmit beamforming and AN scheme. By exploiting the Gauss-Markov fading spectrum to model the feedback delay, we derive a closed-form expression of the upper bound on the secrecy rate loss, where $N_t$ = 2. For a moderate number of antennas where $N_t$ > 2, two special cases, based on the first-order statistics of the noise leakage and large number theory, are explored to approximate the respective upper bounds. In addition, to maintain a constant signal-to-interferenceplus-noise ratio degradation, we analyze the corresponding delay constraint. Furthermore, based on the obtained closed-form expression of the lower bound on the achievable secrecy rate, we investigate an optimal power allocation strategy between the information signal and the AN. The analytical and numerical results obtained based on first-order statistics can be regarded as a good approximation of the capacity that can be achieved at the legitimate receiver with a certain number of antennas, $N_t$. In addition, for a given delay, we show that optimal power allocation is not sensitive to the number of antennas in a high signal-to-noise ratio regime. The simulation results further indicate that the achievable secrecy rate with optimal power allocation can be improved significantly as compared to that with fixed power allocation. In addition, as the delay increases, the ratio of power allocated to the AN should be decreased to reduce the secrecy rate degradation.

• Journal of the Korean Geophysical Society
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• v.3 no.3
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• pp.161-174
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• 2000

Bayesian inversion is a stable approach to infer the subsurface structure with the limited data from geophysical explorations. In geophysical inverse process, due to the finite and discrete characteristics of field data and modeling process, some uncertainties are inherent and therefore probabilistic approach to the geophysical inversion is required. Bayesian framework provides theoretical base for the confidency and uncertainty analysis for the inference. However, most of the Bayesian inversion require the integration process of high dimension, so massive calculations like a Monte Carlo integration is demanded to solve it. This method, though, seemed suitable to apply to the geophysical problems which have the characteristics of highly non-linearity, we are faced to meet the promptness and convenience in field process. In this study, by the Gaussian approximation for the observed data and a priori information, fast Bayesian inversion scheme is developed and applied to the model problem with electric well logging and dipole-dipole resistivity data. Each covariance matrices are induced by geostatistical method and optimization technique resulted in maximum a posteriori information. Especially a priori information is evaluated by the cross-validation technique. And the uncertainty analysis was performed to interpret the resistivity structure by simulation of a posteriori covariance matrix.