• Journal of the Korean GEO-environmental Society
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• v.13 no.10
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• pp.55-62
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• 2012

In this research, the algorithm for simulating specific grain size distribution(GSD) with large diameter granular material was developed using the distinct element analysis program $PFC^{3D}$(Particle Flow Code). This modeling approach can generate the initial distinct elements without clump logic or cluster logic and prevent distinct element from escaping through the confining walls during the process. Finally the proposed distinct element model is used to simulate large triaxial compression test of the rockfill material and we compared the simulation output with lab test results. Simulation results of Assembly showed very well agreement with the GSD of the test sample and numerical modeling of granular material would be possible for various stress conditions using this application through the calibration.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2011.04a
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• pp.419-423
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• 2011

Unlike other non-destructive inspection method, AE Structural defects that are likely to grow in the operation status can be detected, and the advantage of being due to the continuous monitoring of large structures has been widely used to evaluate the stability. AE sensor used to detect sound wave that occurs between 20kHz to 20MHz. and Sound wave result may vary depending on sensor's sensitivity. In this paper, Tensile test conducted on STS 304 and SS400, and tries to detect the crack signal. In tensile test, specimens were conducted using different sensor sensitivity to the same tensile test condition. The crack signal parameters divided into 4 types of communities by conducting cluster analysis. It was demonstrated that crack signal of two sensor is not different by statistical analysis of null hypotheses. Based on the results, waveform of this tension test is crack signal.

• Macromolecular Research
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• v.17 no.2
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• pp.99-103
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• 2009

We evaluated the efficacy of pH-sensitive micelles, formed by methoxy poly(ethylene glycol)-b-poly($\beta$)-amino ester) (PEG-PAE), as carriers for paclitaxel (PIX), a drug currently used to treat various cancers. PTX was successful encapsulated by a film hydration method. Micelles encapsulated more than 70% of the PTX and the size of the PTX-encapsulated micelles (PTX-PM) was less than 150 nm. In vitro experiments indicated that the micelles were unstable below pH 6.5. After encapsulation of PTX within the micelles, dynamic light scattering (DLS) studies indicated that low pH had a similar demicellization effect. An in vitro release study indicated that PTX was slowly released at pH 7.4 (normal body conditions) but rapidly released under weakly acidic conditions (pH 6.0). We demonstrated the safety of micelles from in vitro cytotoxicity tests on HeLa cells and the in vivo anti-tumor activity of PTX-PM in B16F 10 tumor-bearing mice. We concluded that these pH-sensitive micelles have potential as carriers for anti-cancer drugs.

• Journal of Korean Society on Water Environment
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• v.34 no.5
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• pp.537-547
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• 2018

Sediment discharge by rainfall runoff affects water quality in rivers such as turbid water, eutrophication. In order to solve various problems caused by soil loss, it is important to establish a sediment management plan for watersheds and rivers in advance. However, there is a lack of sediment data available for estimating sediment discharge in ungauged basins.. Thus, reasonable research is very important to evaluate and predict the sediment discharge quantitatively. In this study, cluster analysis was conducted to classify gauged watersheds into hydrologically homogeneous groups based on the watershed characteristics. Also, this study suggests a method to efficiently predict the sediment discharge for ungauged basins by developing and evaluating the SDR equations based on the PA-SDR module. As the result, the SDR equations for the classified watersheds were derived to predict the most reasonable sediment discharge of ungauged basins with 0.24 % ~ 10.89 % errors. It was found that the optimal parameters for the gauged basins reflect well characteristic of sediment movement. SDR equations proposed in this study will be available for estimating sediment discharge on ungauged basins. Also it is possible to utilize establishing the appropriate sediment management plan for integrated management of watershed and river in Korea.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.4
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• pp.197-212
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• 2019

The purpose of this study is to identify the maturity stages of venture firms through classification analysis, which is widely used as a big data technique. Venture companies should develop a competitive advantage in the market. And the maturity stage of a company can be classified into five stages. I will analyze a difference in the growth stage of venture firms between the survey response and the statistical classification methods. The firm growth level distinguished five stages and was divided into the period of start-up and declines. A classification method of big data uses popularly k-mean cluster analysis, hierarchical cluster analysis, artificial neural network, and decision tree analysis. I used variables that asset increase, capital increase, sales increase, operating profit increase, R&D investment increase, operation period and retirement number. The research results, each big data analysis technique showed a large difference of samples sized in the group. In particular, the decision tree and neural networks' methods were classified as three groups rather than five groups. The groups size of all classification analysis was all different by the big data analysis methods. Furthermore, according to the variables' selection and the sample size may be dissimilar results. Also, each classed group showed a number of competitive differences. The research implication is that an analysts need to interpret statistics through management theory in order to interpret classification of big data results correctly. In addition, the choice of classification analysis should be determined by considering not only management theory but also practical experience. Finally, the growth of venture firms needs to be examined by time-series analysis and closely monitored by individual firms. And, future research will need to include significant variables of the company's maturity stages.

• Journal of Satellite, Information and Communications
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• v.5 no.2
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• pp.45-49
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• 2010

This paper presents the study on multi-beam large aperture antenna systems for a satellite payload. Multi-beam large antenna provides the universal communication and broadcasting services to personal portable terminals. The hybrid antenna composed of a large reflector and a feed array forms multi-beams. The feed cluster consists of a group of feed elements and each element should be optimized for the appropriate amplitude and phase. The optimization progress for amplitude and phase was performed by GO (Geometrical Optics) and PO (Physical Optics) method. The number of feed elements as well as the power level per element were also optimized to meet the required EIRP (Effective Isotropically Radiated Power). In conclusion, 30m-class reflector and twenty five elements for fifteen beams over Korean Peninsula were designed through the optimization process.

• The Journal of the Korea Contents Association
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• v.13 no.7
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• pp.386-394
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• 2013

The purpose of the current study was to investigate the difference in recreation specialization levels based on the levels of leisure constraint negotiation and to examine the effect of leisure constraint negotiation on recreation specialization. A total of 374 skiers Kyonggi and Kangwon provinces was selected using the cluster sampling method. All respondents were divided into 3 groups based on the levels of leisure constraint negotiation and one-was ANOVA and regression analysis were conducted. The main findings were as follows: First, skiers were divided into 3 groups(high, middle, low) by the K-mean cluster analysis. Second, there were differences in past experience, centrality of life, financial investment, and overall recreation specialization based on the levels of leisure constraint negotiation. Finally, leisure constrain negotiation had a positive effect on recreation specialization.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.5
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• pp.385-392
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• 2002

Collaborative filtering method for personalization can suggest new items and information which a user hasn t expected. But there are some problems. Not only the steps for calculating similarity value between each user is complex but also it doesn t reflect user s interest dynamically when a user input a query. In this paper, classifying users by their interest makes calculating similarity simple. We propose the a1gorithm for readjusting user s interest dynamically using the profile and Bayesian learning. When a user input a keyword searching for a item, his new interest is readjusted. And the user s profile that consists of used key words and the presence frequency of key words is designed and used to reflect the recent interest of users. Our methods of adjusting user s interest using the profile and Bayesian learning can improve the real satisfaction of users through the experiment with data set, collected in University s library. It recommends a user items which he would be interested in.

• Journal of the Korean Data and Information Science Society
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• v.24 no.1
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• pp.41-51
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• 2013

In the Information age, internet addiction has been a big issue in a modern society. The adverse effects of the internet addiction have been increasing at an exponential speed. Along with a great variety of internet-connected device supplies, K-scale diagnostic criteria have been used for the internet addiction self-diagnose tests in the high-speed wireless Internet service, netbooks, and smart phones, etc. The K-scale diagnostic criteria needed to be changed to meet the changing times, and the diagnostic criteria of K-scale was changed in March, 2012. In this paper, we analyze the internet addiction and K-scale features on the actual condition of Gyeongbuk collegiate areas using the revised K-scale diagnostic criteria in 2012. The diagnostic method on internet addiction is measured by the respondents' subjective estimation. Willful error of the respondents can be occurred to hide their truth. In this paper, we add the survey response to the trusted reliability values to reduce response errors on the K-scale on the K-scale, and enhance the reliability of the analysis.

• Journal of the Korean Data and Information Science Society
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• v.28 no.2
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• pp.395-406
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• 2017

The purpose of this study is to identify the pattern of daily electricity demand through clustering and classification. The hourly data was collected by KPS (Korea Power Exchange) between 2008 and 2012. The time trend was eliminated for conducting the pattern of daily electricity demand because electricity demand data is times series data. We have considered k-means clustering, Gaussian mixture model clustering, and functional clustering in order to find the optimal clustering method. The classification analysis was conducted to understand the relationship between external factors, day of the week, holiday, and weather. Data was divided into training data and test data. Training data consisted of external factors and clustered number between 2008 and 2011. Test data was daily data of external factors in 2012. Decision tree, random forest, Support vector machine, and Naive Bayes were used. As a result, Gaussian model based clustering and random forest showed the best prediction performance when the number of cluster was 8.