• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.1-7
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• 2012

Cognitive radio, a new paradigm for wireless communication, is being recently expected to support various types of multimedia traffics. To guarantee Quality of Service (QoS) from SUs, a static packet priority policy can be considered. However, this approach can easily satisfy Quality of Service of high priority application while that of lower priority applications is being degraded. In the paper, we propose a fuzzy-based dynamic packet scheduling algorithm to support multimedia traffics in which the dynamic packet scheduler modifies priorities of packets according to Fuzzy-rules with the information of priority and delay deadline of each packet, and determines which packet would be transmitted through the channel of the primary user in the next time slot in order to reduce packet loss rate. Our simulation result shows that packet loss rate can be improved through the proposed scheme when overall traffic load is not heavy.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.1
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• pp.81-86
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• 2005

In this study, we introduce a new category of fuzzy inference systems based on information granulation to carry out the model identification of complex and nonlinear systems. Informally speaking, information granules are viewed as linked collections of objects (data, in particular) drawn together by the criteria of proximity, similarity, or functionality Granulation of information with the aid of Hard C-Means (HCM) clustering help determine the initial parameters of fuzzy model such as the initial apexes of the membership functions and the initial values of polynomial functions being used in the premise and consequence part of the fuzzy rules. And the initial parameters are tuned effectively with the aid of the genetic algorithms(GAs) and the least square method (LSM). An aggregate objective function with a weighting factor is also used in order to achieve a balance between performance of the fuzzy model. The proposed model is evaluated with using a numerical example and is contrasted with the performance of conventional fuzzy models in the literature.

• Journal of the Korean Geotechnical Society
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• v.16 no.1
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• pp.75-81
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• 2000

The anisotropy of soils has an important effect on stress-strain behavior. In this study, an attempt has been made to implement artificial neural network model for modeling the stress-strain relationship and predicting the undrained shear strength of normally consolidated clay with varying consolidation pressure ratios. The multi-layer neural network model, adopted in this study, utilizes the error back-propagation loaming algorithm. The artificial neural networks use the results of undrained triaxial test with various consolidation pressure ratios and different effective vertical consolidation pressure fur learning and testing data. After learning from a set of actual laboratory testing data, the neural network model predictions of the undrained shear strength of the normally consolidated clay are found to agree well with actual measurements. The predicted values by the artificial neural network model have a determination coefficient$(r^2)$ above 0.973 compared with the measured data. Therefore, this results show a positive potential for the applications of well-trained neural network model in predicting the undrained shear strength of cohesive soils.

• 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.