• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.11B no.2
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• pp.15-21
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• 2001

This paper presents an improved characteristic analysis methodology for a 5-phase hybrid stepping motor. The basic approach is based on the use of equivalent magnetic circuit taking into account the localized saturation throughout the hybrid stepping motor. The finite element method(FEM) is used to generate the magnetic circuit parameters for the complex stator and rotor teeth and airgap considering the saturation effects in tooth and poles. In addition, the neural network is used to map a change of parameters and predicts their approximation. Therefore, the proposed method efficiently improves the accuracy of analysis by using the parameter characterizing localized saturation effects and reduces the computational time by using the neural network. An improved circuit model of 5-phase hybrid stepping motor is presented and its application is provided to demonstrate the effectiveness of the proposed method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.227-233
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• 1996

The Inverted Pendulum has been one of most popular nonlinear dynamic systems for the exploration of control techniques. This paper presents a new linear optimal control techniques and nonlinear neural network learning methods. The multiayered neural networks are used to add nonlinear effects on the linear optimal regulator(LQR). The new regulator can compensate nonlinear system uncertainties that are not considered in the LQR design, and can tolerated a wider range of uncertainties than the LQR alone. The new regulator has two neural networks for modeling and control. The neural network for modeling is used to obtain a more accurate model than the given mathematical equations. The neural network for control is used to overcome deficiencies by adding corrections to the linear coefficients of the LQR and by adding nonlinear effects on the LQR. Computer simulations are performed to show the applicability and a more robust regulator than the LQR alone.

• Communications for Statistical Applications and Methods
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• v.30 no.5
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• pp.517-530
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• 2023

Recent studies revealed that fine dust in ambient air may cause various health problems such as respiratory diseases and cancer. To prevent the toxic effects of fine dust, it is important to predict the concentration of fine dust in advance and to identify factors that are closely related to fine dust. In this study, we developed a Bayesian network model for predicting PM10 concentration in Seoul, Korea, and visualized the relationship between important factors. The network was trained by using air quality and meteorological data collected in Seoul between 2018 and 2021. The study results showed that current PM10 concentration, season, carbon monoxide (CO) were the top 3 effective factors in 24 hours ahead prediction of PM10 concentration in Seoul, and that there were interactive effects.

• Journal of Family Resource Management and Policy Review
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• v.17 no.4
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• pp.85-100
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• 2013

The purposes of this study are to explore the effect of the network characteristics of Healthy Family Support Center on its performance, and also to investigate the mediating effect of the organizational properties on the performance. We used the data from 148 healthy family support centers in National Survey in Korea. The analytic sample for this study consists of 102 responses.(response rate=68.9%) Multivariate regression model estimated the effects of the network's structural, interactive and functional characteristics and the interaction between the network's characteristics and organizational properties on the performance The findings of this study demonstrate that healthy family support centers with higher closeness centrality and with better functional characteristics reported more performances. Moreover, Centers that are more independent in organizational properties showed higher performances. However, the findings did not show that the interaction between the network's characteristics and organizational properties mediates on the performance.

• The KIPS Transactions:PartC
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• v.12C no.6 s.102
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• pp.839-846
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• 2005

Recently broadband convergence network technology is emerging as an integrated network of telecommunication, broadcasting and Internet. But there are various threats as side effects against the growth of information technology, and malicious codes such af Internet worms may bring about confusions to upset a national backbone network. In this paper, we survey the traditional spreading models and propose a new worm spreading model on Internet environment. We also analyze the spreading effects due to tile spread period and the response period of Internet worms. The proposed model leads to a better prediction of the scale and speed of worm spreading. It can be applied to high-speed network such as broadband convergence network.

• Smart Structures and Systems
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• v.32 no.2
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• pp.83-99
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• 2023

The temperature prediction approaches of three important locations in an operational longitudinal slab track-bridge structure by using three typical neural network methods based on the field measuring platform of four meteorological factors and internal temperature. The measurement experiment of four meteorological factors (e.g., ambient temperature, solar radiation, wind speed, and humidity) temperature in the three locations of the longitudinal slab and base plate of three important locations (e.g., mid-span, beam end, and Wide-Narrow Joint) were conducted, and then their characteristics were analyzed, respectively. Furthermore, temperature prediction effects of three locations under five various meteorological conditions are tested by using three neural network methods, respectively, including the Artificial Neural Network (ANN), the Long Short-Term Memory (LSTM), and the Convolutional Neural Network (CNN). More importantly, the predicted effects of solar radiation in four meteorological factors could be identified with three indicators (e.g., Root Means Square Error, Mean Absolute Error, Correlation Coefficient of R2). In addition, the LSTM method shows the best performance, while the CNN method has the best prediction effect by only considering a single meteorological factor.

• The Journal of the Korea Contents Association
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• v.14 no.12
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• pp.753-763
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• 2014

After retirement, retirees are exposed to many changes. But, one of the most influential factor on retirement is Social network. Social network is making various relationships with many people. This consists of functional feature and structure feature. This study to systematically investigate social network changes of pre- and post-retirement by using two features. We utilized 2008~2012 'Longitudinal study of ageing' and selected 1,569 retirees above 45 years old as a final subject. This study used STATA 12.0 program for analysing frequency and descriptive statistic. At first, we analyzed personal characteristics and affecting factor on social network of retirees through Panel logit model and fixed effects regression model. Second, we applied multiple panel logit model and fixed effects model to learn factor affecting employment and social network changes. We found that a number of social activities affects social network in the structure feature and support from sons and daughters also influences social network in the functional feature after retirement.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.639-642
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• 2015

As attack to routing function on MANET(Mobile Ad-Hoc Network), hole attack make cause some critical effects. MANET is easily influenced with hole attack and can be critically effected on transmission performance, because it is configured with terminal device as temporary network and dose not have effective means for malicious attack. In this paper, effects of grayhole attack to network performance on MANTE is analyzed with computer simulation. Voice traffic is used in simulation, effects of grayhole attack is compaerd with blackhole attack. The method and result of this paper can be used for data to study grayhoke attack.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.578-581
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• 2014

Blackhole attack, a kinds of attacks to routing function, can cause critical effects to network transmission function, Especially, on MANET(Mobile Ad-hoc Network) which it is not easy to prepare functions to respond malicious intrusion, transmission functions of entire networks could be degraded. In this paper, effects of blackhole attack to network transmission performance is analyzed on lattice structured MANET. Specially, performance is measured for various location of blackhole attack on lattice MANET, and compared with the performance of random structured MANET. This paper is done with computer simulation, VoIP(Voice over Internet Protocol) traffic is used in simulation. The results of this paper can be used for data to deal with blackhole attack.

• The Journal of Economics, Marketing and Management
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• v.7 no.4
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• pp.20-32
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• 2019

Purpose - There have been many studies regarding the preceding factors required for success of start-up. The purpose of this study is to verify one of the paths by which the individual characteristics of founders and governmental support lead to enhanced start-up performance, via entrepreneurship and network building. Research design, data, methodology - Data for this study was collected from surveys of 332 founders throughout South Korea, and statistical analyses of this data were performed using SPSS 22.0 and Smart PLS 2.0. To verify our hypothesis, path analysis was performed using a structural equation model. Results -The variables, entrepreneurial self-esteem and experience were found to have positive effects on the entrepreneurship and networks. Secondly, governmental support did not have significant positive effect on entrepreneurship, but it did have positive effect on networking. Thirdly, entrepreneurship and networking were confirmed to have positive effects on both the utilization of opportunities and financial performance, which are variables indicating start-up performance. Conclusion - Although founder's characteristics are important for success of start-up, it is also critically important to actively utilize governmental support. Notably, many founders suffer from inadequate networks. They would be able to enhance their start-up performance by utilizing various governmental support programs to reinforce their network capabilities.