• Transactions of the Korean Society of Mechanical Engineers B
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• v.35 no.6
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• pp.649-656
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• 2011

A model for the numerical simulation of lithium-ion batteries (LIBs) is developed for use in battery cell design, with a view to improving the performances of such batteries. The model uses Newman-type electrochemical and transfer $theories^{(1,2)}$ to describe the behavior of the lithium-ion cell, together with the Levenberg-Marquardt optimization scheme to estimate the performance or design parameters in nonlinear problems. The mathematical model can provide an insight into the mechanism of LIB behavior during the charging/discharging process, and can therefore help to predict cell performance. Furthermore, by means of least-squares fitting to experimental discharge curves measured at room temperature, we were able to obtain the values of transport and kinetic parameters that are usually difficult to measure. By comparing the calculated data with the life-test discharge curves (SB LiMotive cell), we found that the capacity fade is strongly dependent on the decrease in the reaction area of active materials in the anode and cathode, as well as on the electrolyte diffusivity.

• Journal of Digital Contents Society
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• v.9 no.4
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• pp.661-667
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• 2008

The dynamics of business cycles has been changed by the macroscopic economic forces because of the introduction of new technical know-how each year. These the dynamics of business has a significant influence on the investment of enterprise in the information communication field. Today, the most important goal of the IT investment is simply not to lower the production cost any more, but to improve the usefulness for the customers and partners in order to obtain the optimized mass products. Therefore, the enterprises have been concentrating their all abilities on the automation, integration, and optimization of business process using BPM. In addition, they are concentrating their efforts on the business expansion by approaching the technical aspect using RFID application system. However, in order to accomplish a successful enterprise ability, the technical view, business process view, and organization view must be considered together. We suggested the method considering organization view, via the technical element, i.e., RFID system for approaching the business process. Furthermore, we tried the optimization of assignment using Context Analysis methodology and proposed the method to reduce the element with respect to the time, human, and expense by applying the Case Study method that minimizes the iteration times through the transmitted processing procedure and type. The proposed method gave us the expectation that it will bring out the innovative improvement with respect to the time, expense, quality, and customer's satisfaction in the process from the analysis of business process to the analysis and design of system.

• 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.

• Korean Journal of Food Science and Technology
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• v.21 no.5
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• pp.676-685
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• 1989

Optimal operating conditions of on-farm red pepper dryer were searched by using the simulation-optimization algorithm combining the drying and quality deterioration models of red pepper with Box's complex method. Determination of control variables such as air temperature, air recycle ratio and air flow rate was based on a criterion of minimizing energy consumption under the constrainst conditions that satisfied the specified color retention of carotenoids. As quality constraint was stricter, energy consumption increased and total drying time decreased with lower recycle ratio and higher air flow rate Product mixing during drying was found to be able to improve the energy efficiency and product quality. Currently used air flow rate was assessed to be increased for the optimal operation. Two stage drying at the fixed optimal air flow rate was proven to be useful means for further saying of energy consumption. In the optimal bistaged drying, the second stage began at about one third of the total drying time and low air temperature in the first stage Increased to a high value and air recycle ratio increased slightly in the second stage. Optimal control variable scheme could be explained by the dryer performance and the carotenoids destruction kinetics in red pepper drying.

• Korean Journal of Food Science and Technology
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• v.20 no.2
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• pp.272-279
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• 1988

Kinetics of ascorbic acid destruction and browning were evaluated by the dynamic test using actual drying data in order to apply in the optimization of food dehydration. Radish was chosen as a test material because it has many typical quality characteristics during drying. Radish was dried in the cabinet dryer with being measured in moisture, food temperature, ascorbic acid and browning. Using moisture and temperature history, proposed kinetic model was integrated and parameters of the model were searched by the iteration scheme to show minimum discrepancy between predicted and experimental data. Ascorbic acid destruction and browning were represented by first and zero order reaction respectively. Arrhenius equation was used to describe temperature dependence. Several mathematical functions of moisture dependence were compared in the model simplicity and residual sum of square. Attained kinetic models were analyzed as functions of temperature and moisture. Rate of ascorbic acid destruction was low at high moisture content, increased with moisture decrease to show a maximum at the moisture of $9{\sim}12g/g$ dry solid, and then decreased up to full dryness. Browning rate increased with moisture decrease to show a sharp maximum at $4{\sim}6g/g$ dry solid and decreased with further moisture decrease.

• Journal of Biosystems Engineering
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• v.29 no.4
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• pp.341-346
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• 2004

Recent livestock people concern not only increase of production, but also superior quality of animal-breeding environment. So far, the optimization of the breeding and air environment has been focused on the production increase. In the very near future, the optimization will be emphasized on the environment for the animal welfare and health. Especially, cattle farming demands the precision livestock farming and special attention has to be given to the management of feeding, animal health and fertility. The management of individual animal is the first step for precision livestock farming and animal welfare, and recognizing each individual is important for that. Though electronic identification of a cattle such as RFID(Radio Frequency Identification) has many advantages, RFID implementations practically involve several problems such as the reading speed and distance. In that sense, computer vision might be more effective than RFID for the identification of an individual animal. The researches on the identification of cattle via image processing were mostly performed with the cows having black-white patterns of the Holstein. But, the native Korean and Japanese cattle do not have any definite pattern on the body. The purpose of this research is to identify the Japanese black cattle that does not have a body pattern using computer vision technology and neural network algorithm. Twelve heads of Japanese black cattle have been tested to verify the proposed scheme. The values of input parameters were specified and then computed using the face images of cattle. The images of cattle faces were trained using associate neural network algorithm, and the algorithm was verified by the face images that were transformed using brightness, distortion, and noise factors. As a result, there was difference due to transform ratio of the brightness, distortion, and noise. And, the proposed algorithm could identify 100% in the range from -3 to +3 degrees of the brightness, from -2 to +4 degrees of the distortion, and from 0% to 60% of the noise transformed images. It is concluded that our system can not be applied in real time recognition of the moving cows, but can be used for the cattle being at a standstill.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.1
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• pp.51-66
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• 2022

SST (Sea Surface Temperature) is based on the atmosphere-ocean interaction, one of the most important mechanisms for the Earth system. Because it is a crucial oceanic and meteorological factor for understanding climate change, gap-free grid data at a specific spatial and temporal resolution is beneficial in SST studies. This paper examined the production of daily SST grid maps from 137 stations in 2020 through the ordinary kriging with variogram optimization and their accuracy assessment. The variogram optimization was achieved by WLS (Weighted Least Squares) method, and the blind tests for the interpolation accuracy assessment were conducted by an objective and spatially unbiased sampling scheme. The four-round blind tests showed a pretty high accuracy: a root mean square error between 0.995 and 1.035℃ and a correlation coefficient between 0.981 and 0.982. In terms of season, the accuracy in summer was a bit lower, presumably because of the abrupt change in SST affected by the typhoon. The accuracy was better in the far seas than in the near seas. West Sea showed better accuracy than East or South Sea. It is because the semi-enclosed sea in the near seas can have different physical characteristics. The seasonal and regional factors should be considered for accuracy improvement in future work, and the improved SST can be a member of the SST ensemble around South Korea.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4678-4702
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• 2018

Traffic Matrix estimation has always caught attention from researchers for better network management and future planning. With the advent of high traffic loads due to Cloud Computing platforms and Software Defined Networking based tunable routing and traffic management algorithms on the Internet, it is more necessary as ever to be able to predict current and future traffic volumes on the network. For large networks such origin-destination traffic prediction problem takes the form of a large under- constrained and under-determined system of equations with a dynamic measurement matrix. Previously, the researchers had relied on the assumption that the measurement (routing) matrix is stationary due to which the schemes are not suitable for modern software defined networks. In this work, we present our Compressed Sensing with Dynamic Model Estimation (CS-DME) architecture suitable for modern software defined networks. Our main contributions are: (1) we formulate an approach in which measurement matrix in the compressed sensing scheme can be accurately and dynamically estimated through a reformulation of the problem based on traffic demands. (2) We show that the problem formulation using a dynamic measurement matrix based on instantaneous traffic demands may be used instead of a stationary binary routing matrix which is more suitable to modern Software Defined Networks that are constantly evolving in terms of routing by inspection of its Eigen Spectrum using two real world datasets. (3) We also show that linking this compressed measurement matrix dynamically with the measured parameters can lead to acceptable estimation of Origin Destination (OD) Traffic flows with marginally poor results with other state-of-art schemes relying on fixed measurement matrices. (4) Furthermore, using this compressed reformulated problem, a new strategy for selection of vantage points for most efficient traffic matrix estimation is also presented through a secondary compression technique based on subset of link measurements. Experimental evaluation of proposed technique using real world datasets Abilene and GEANT shows that the technique is practical to be used in modern software defined networks. Further, the performance of the scheme is compared with recent state of the art techniques proposed in research literature.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.7
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• pp.1589-1596
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• 2013

Recently, spectral efficiency or reliability is required to be improved in the scenario of multiple access. In this paper, we consider a scenario where two source nodes access one destination node. Different with conventional multiple access studies, in our research, a part of the allocated resource is shared by two source nodes and this scheme is called partial multiplexing. Let $R_s$ denote the ratio of the amount of the shared resource to that of the resource allocated to each user. We analyze and optimize the performance of the partial multiplexing in term of $R_s$. We show that the optimal $R_s$ to maximize the throughput is 1 or 0 based on approximated bit error rate (BER). In addition, if we set a constraint on frame error rate (FER), $R_s$ can have a value between 0 and 1. We also find the approximated $R_s$ to meet the constraint as a closed form. Partial multiplexing can be a novel multiple access scheme.

• Journal of Korean Society of Steel Construction
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• v.19 no.1
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• pp.15-27
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• 2007

Over the past decade, labor costs have increased relative to the cost of material hardware according to analysts in the construction industry. Therefore, the minimum weight design, which has been widely adopted in the literature for the optimal design of steel structures, is no longer the most economical construction approach. Presently, although connection- related costs is crucial in determining the most cost-effective steel structures, most studies on this subject focused on minimum-weight design or engaged in higher analysis. Therefore, in this study, we proposed a fabrication scheme for the most cost-effective moment-resisting steel frame structures that resist lateral loads without compromising overall stability. The proposed approach considers the cost of steel products, fabrication, and connections within the design process. The optimal design considered construction realities, with the optimal trade-off between the number of moment connections and total cost was achieved by reducing the number of moment connections and rearranging them using the combination of analysis that includes shear, displacement and interaction value based on the LRFD code and optimization scheme based on genetic algorithms. In this study, we have shown the applicability and efficiency in the examples that considered actual loading conditions.