• Applied Chemistry for Engineering
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• v.26 no.6
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• pp.659-665
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• 2015

Loading of hydrophobic ${\alpha}$-tocopherol into nanostructured lipid carrier (NLC) was performed for improving its oxidative stability. First, various NLCs with different constituents and mixing ratios were prepared and their characteristics were investigated. While the stable NLCs were made when cetyl palmitate (CP) or glyceryl monosterate (GMS) was used as a solid lipid, the phase separation occurred in the NLCs consisting of stearic acid. Particle sizes of the NLCs were several hundreds of nanometers and the size decreased with increasing the ratio of solvent to lipid. It was examined from DSC thermogram and anisotropy test that the degree of crystallinity of the lipid phase decreased and the lipid matrix became less ordered when octyldodecanol, a long chain fatty alcohol, was added into the solid lipid. The oxidative stability of ${\alpha}$-tocopherol in NLC was remarkably improved compared to that in solution or emulsion under high temperature ($45^{\circ}C$) and UV radiation, which was verified through DPPH test and peroxide value measurement.

• The Journal of Korean Association of Computer Education
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• v.17 no.1
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• pp.1-12
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• 2014

Since students' behaviors during e-learning are automatically stored in LMS(Learning Management System), the LMS log data convey the valuable information of students' engagement. The purpose of this study is to develop a prediction model of e-learning course dropout by utilizing LMS log data. Log data of 578 college students who registered e-learning courses in a traditional university were used for the logistic regression analysis. The results showed that attendance and study time were significant to predict dropout, and the model classified between dropouts and completers of e-learning courses with 96% accuracy. Furthermore, the feasibility of early detection of dropouts by utilizing the model were discussed.

• Journal of Digital Contents Society
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• v.19 no.9
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• pp.1751-1758
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• 2018

An integrated medical information system that integrates systems consisting of different environments centered on hospital information systems should be provided as a system that prioritizes the improvement of the quality of medical services, customer satisfaction, and patient safety. The RBAC-based medical information system is granted the access right according to task type, role, and rules. Through this, it is possible to use SMS channel, medical reservation and cancellation, customized statistics, and CRM / EMR interworking service using multi-channel to enable communication service without help of counselor and reduce the default rate of reservation patient, Operational improvement services can be extended to medical staff, patients and their families, as well as expanding to important decisions for patients.

• Journal of the Korea Society of Computer and Information
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• v.19 no.8
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• pp.11-18
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• 2014

In This paper, we propose the unsupervised learning and fuzzy logic-based coupled data classification method base on ART. The unsupervised learning-based data classification helps improve the grouping technique, but decreases the processing efficiency. However, the data classification requires the decision technique to induce high success rate of data classification with optimal threshold. Therefore it is also necessary to solve the uncertainty of the threshold decision. The proposed method deduces the optimal threshold with the designing of fuzzy parameter and rules. In order to evaluate the proposed method, we design the simulation model with the GPCR(G protein coupled receptor) data in cloud computing environment. Simulation results verify the efficiency of our method with the high recognition rate and low processing time.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.1-8
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• 2014

Cloud computing helps big data processing to make various information using IT resources. The government has to start the RPS(Renewable Portfolio Standard) and induce the production of electricity using renewable energy equipment. And the government manages system to gather big data that is distributed geographically. The companies can purchase the REC(Renewable Energy Certificate) to other electricity generation companies to fill shortage among their duty from the system. Because of the RPS use voluntary competitive market in REC trade and the prices have the large variation, RPS is necessary to predict the equitable REC price using RPS big data. This paper proposed REC price prediction method base on fuzzy logic using the price trend and trading condition infra in REC market, that is modeled in cloud computing environment. Cloud computing helps to analyze correlation and variables that act on REC price within RPS big data and the analysis can be predict REC price by simulation. Fuzzy logic presents balanced REC average trading prices using the trading quantity and price. The model presents REC average trading price using the trading quantity and price and the method helps induce well-converged price in the long run in cloud computing environment.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.31 no.6
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• pp.368-378
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• 2019

Logic trees for probabilistic tsunami hazard assessment include numerous variables to take various uncertainty on earthquake generation into consideration. Results from the hazard assessment vary in different way as more variables are considered in the logic tree. This study is conducted to estimate the effects of various scaling laws and fault parameters on tsunami hazard at the nearshore of Busan. Active fault parameters, such as strike angle, dip angle and asperity, are adjusted in the modelling of tsunami propagation, and the numerical results are used in the sensitivity analysis. The influence of strike angle to tsunami hazard is not as much significant as it is expected, instead, dip angle and asperity show a considerable impact to tsunami hazard assessment. It is shown that the dip angle and the asperity which determine the initial wave form are more important than the strike angle for the assessment of tsunami hazard in the East Sea.

• Science of Emotion and Sensibility
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• v.10 no.1
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• pp.37-47
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• 2007

Color planning system can be treated as a decision support system which includes both the recommendation of main color and harmonious colors. In this paper, we propose techniques that are useful to enhance the harmonious color recommendation with the main color selected by user. In order to reflect the knowledge about suggestion of harmonious colors, we use Ostwald color harmony theory, that is very systematical and easy to implement. Actually, Ostwald color space is similar to HMMD color model in MPEG-7. Due to the similarity between two color spaces, Ostwald color space can be represented as a virtual HMMD color space. Accordingly, we propose a technique to align the HMMD color space with Ostwald color space, thereby it is capable of enhancing a performance to search the harmonious colors according to Ostwald harmony theory. For recommendation of delicate and more exquisite harmonious colors in equal hue plane, we made the virtual color space continuous. The system can recommend various harmonious colors according to Ostwald color harmony. He(she) can select harmonious colors among the suggestions from the system.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.37 no.1
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• pp.83-91
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• 2000

This paper presents a new technique to reduce a large interconnect circuit with tens of thousands of elements into the one that is small enough to be analyzed by circuit simulators such as SPICE. This technique takes a fundamentally different approach form the conventional methods based on the interconnect circuit structure analysis and several rules based on the Elmore time constant. The time moments are computed form the circuit consisting of the interconnect circuit and the CMOS gate driver model computed by the AWE technique. Then, the equivalent RC circuit is synthesized from those moments. The characteristics of the driving CMOS gate can be reflected with the high degree of accuracy and the size of the compressed circuit is determined by the number of output nodes regardless of the size of the original interconnect circuits. This technique has been implemented in C language, applied to several interconnect circuits driven by a 0.5${\mu}m$ CMOS gate and the equivalent RC circuits with more than 99% reduction ratio and accuracy with 1 ~ 10% error in therms of propagation delays were obtained.

• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.153-160
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• 2005

It is within bounds to say that the mood expressed in the Scenes of 3D Animation influences by mostly setting up of 3D CG lighting. Tn the context of CG, lighting is the process of illuminating digital scenes in an artistic and technical manner so the audience can perceive what the director intends to display on the screen with the appropriate clarity and mood. The lighting has the role of making the scenes beautiful and harmonious as an aesthetics of light and color created and controlled by people. It can be also stylized in symbolic and metaphorical methods environmental mood which we pursue to expose and story which we want to express. It thus appears that the concept of lighting style is intimately related to the particular context and art direction of animation film. But unfortunately, there are no foolproof formulas to the process of lighting a scene. In short, the lighting contributes to define the style of the scene as a conditional lighting setups' elements including position, color, intensity, shadow's area and scope. But at the same time, we must not overlook the artistic aspects that the lighting might suggest over all moods the animation genre and the style of scene like tranquility, suspense, and high-drama.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.473-478
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• 2013

In this paper, we develop the Heavy Rain Advisory Decision Model based on intelligent neuro-fuzzy algorithm RBFNNs by using KLAPS(Korea Local Analysis and Prediction System) Reanalysis data. the prediction ability of existing heavy rainfall forecasting systems is usually affected by the processing techniques of meteorological data. In this study, we introduce the heavy rain forecast method using the pre-processing techniques of meteorological data are in order to improve these drawbacks of conventional system. The pre-processing techniques of meteorological data are designed by using point conversion, cumulative precipitation generation, time series data processing and heavy rain warning extraction methods based on KLAPS data. Finally, the proposed system forecasts cumulative rainfall for six hours after future t(t=1,2,3) hours and offers information to determine heavy rain advisory. The essential parameters of the proposed model such as polynomial order, the number of rules, and fuzzification coefficient are optimized by means of Differential Evolution.