• Journal of Korean Society of Rural Planning
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• v.15 no.1
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• pp.47-59
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• 2009

The aim of this study is to analyze the green-tourism centrality considering spatial interaction using Gravity Model and social network method. The degree centrality and prestige centrality were applied as green-tourism centrality index. The rural amenity resources and human resources were counted as attraction factors, and a distance among villages was used as friction factor in gravity model. The weights of rural tourism amenity resources were calculated using the analytic hierarchy process(AHP) method and applied to evaluate green-tourism potentiality. The distance was measured with the shortest path among villages using geographic information system(GIS) network analysis. The spatial interaction from gravity model were employed as link weights between nodal points; a pair villages. Using the spatial interaction, the degree-centrality and prestige-centrality indices were calculated by social network analysis and demonstrated possibility of developing integrated green-tourism region centered on high centrality villages.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.5
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• pp.268-276
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• 2003

In this paper, we present a new control and monitoring technique for a power system using CAN(Controller Area Network). Feedback control systems having co'ntrol loops closed through a network(i.e. Ethernet, ControlNet, CAN) are called NCSs(Networked Control Systems). The major problem of NCSs is the variation of stability property according to time delay including network-induced delay and computation delay in nodes. We present a new stability analysis method of NCSs with time delay exploiting a state-space model of LTI(Linear Time Invariant) interconnected systems. The proposed method can determine a proper sampling period of NCSs that preserves stability performance even in NCSs with a dynamic controller. We design CAN nodes which can transmit control and monitoring data through CAN bus and apply these to NCSs for a power system. The results of the experiment validate effectiveness of our control and monitoring technique for a power system.

• Journal of the Korean Society of Clothing and Textiles
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• v.40 no.6
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• pp.1034-1044
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• 2016

This study seeks a method to objectively evaluate sensibility based on Big Data in the field of design. In order to do so, this study examined the sensibility responses on design factors for the public through a network analysis of texts displayed in social media. 'Hanbok', a formal clothing that represents Korea, was selected as the subject for the research methodology. We then collected 47,677 keywords related to Hanbok from 12,000 posts on Naver blogs from January $1^{st}$ to December $31^{st}$ 2015 and that analyzed using social matrix (a Big Data analysis software) rather than using previous survey methods. We also derived 56 key-words related to design elements and sensibility responses of Hanbok. Centrality analysis and CONCOR analysis were conducted using Ucinet6. The visualization of the network text analysis allowed the categorization of the main design factors of Hanbok with evaluation terms that mean positive, negative, and neutral sensibility responses. We also derived key evaluation factors for Hanbok as fitting, rationality, trend, and uniqueness. The evaluation terms extracted based on natural language processing technologies of atypical data have validity as a scale for evaluation and are expected to be suitable for utilization in an index for sensibility evaluation that supplements the limits of previous surveys and statistical analysis methods. The network text analysis method used in this study provides new guidelines for the use of Big Data involving sensibility evaluation methods in the field of design.

• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.620-623
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• 2000

A very simple control approach using neural network for the robust position control of a Permanent Magnet Synchronous Motor(PMSM) is presented The linear quadratic controller plus feedforward neural network is employed to obtain the robust PMSM system approximately linearized using field-orientation method for an AC servo. The neural network is trained in on-line phases and this neural network is composed by a fedforward recall and error back-propagation training. Since the total number of nodes are only eight this system can be easily realized by the general microprocessor. During the normal operation the input-output response is sampled and the weighting value is trained multi-times by error back-propagation method at each sample period to accommodate the possible variations in the parameters or load torque. And the state space analysis is performed to obtain the state feedback gains systematically. IN addition the robustness is also obtained without affecting overall system response. This method is realized by a floating-point Digital Singal Processor DS1102 Board (TMS320C31) The basic DSP software is used to write C program which is compiled by using ANSI-C style function prototypes.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.3
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• pp.1-8
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• 1998

In this paper, we propose a Neural Call Admission Control (CAC) method using a Sparse Distributed Memory(SDM). CAC is a key technology of TM network traffic control. It should be adaptable to the rapid and various changes of the ATM network environment. conventional approach to the ATM CAC requires network analysis in all cases. So, the optimal implementation is said to be very difficult. Therefore, neural approach have recently been employed. However, it does not mett the adaptability requirements. because it requires additional learning data tables and learning phase during CAC operation. We have proposed a neural network CAC method based on SDM that is more actural than conventioal approach to apply it to CAC. We compared it with previous neural network CAC method. It provides CAC with good adaptability to manage changes. Experimenatal results show that it has rapid adaptability and stability without additional learning table or learning phase.

• Transactions of Materials Processing
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• v.6 no.6
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• pp.482-488
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• 1997

New carbon equivalent equation for the better prediction for the better prediction of roll force in a continuous hot strip mill has been formulated by applying a neural network method. In predicting roll force of steel strip, carbon equivalent equation which normalize the effects of various alloying elements by a carbon equivalent content is very critical for the accurate prediction of roll force. To overcome the complex relationships between alloying elements and operational variables such as temperature, strain, strain rate and so forth, a neural network method which is effective for multi-variable analysis was adopted in the present work as a tool to determine a proper carbon equivalent equation. The application of newly formulated carbon equivalent equation has increased prediction accuracy of roll force significantly and the effectiveness of neural network method is well confirmed in this study.

• ETRI Journal
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• v.42 no.5
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• pp.799-804
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• 2020

Network security situation prediction is difficult due to its strong uncertainty, but DS evidence theory performs well in solving the problem of uncertainty. Based on DS evidence theory, this study analyzed the prediction of the network security situation, designed a prediction model based on the improved DS evidence theory, and carried out a simulation experiment. The experimental results showed that the improved method could predict accurately in the case of a large conflict, and had strong anti-jamming abilities as compared with the original method. The experimental results prove the effectiveness of the improved method in the prediction of the network security situation and provide some theoretical basis for the further application of DS evidence theory.

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.113-116
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• 2021

As artificial intelligence technologies, including deep learning, develop, these technologies are being introduced to code similarity analysis. In the traditional analysis method of calculating the graph edit distance (GED) after converting the source code into a control flow graph (CFG), there are studies that calculate the GED through a trained graph neural network (GNN) with the converted CFG, Methods for analyzing code similarity through CNN by imaging CFG are also being studied. In this paper, to determine which approach will be effective and efficient in researching code similarity analysis methods using artificial intelligence in the future, code similarity is measured through funcGNN, which measures code similarity using GNN, and Siamese Network, which is an image similarity analysis model. The accuracy was compared and analyzed. As a result of the analysis, the error rate (0.0458) of the Siamese network was bigger than that of the funcGNN (0.0362).

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.10
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• pp.678-689
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• 2004

The major concern of networked control system is network uncertainties such as time delay and data loss. Because these uncertainties may degrade the performance of networked control system and destabilize the entire system. Therefore, the performance and the stability variation of networked control system due to network uncertainties must be considered first in designing networked control system. In particular, the stability analysis of networked control system is most important issue since time delay and data loss can make the overall systems unstable. In this paper, we present a new stability analysis method of networked control system with time delay and data loss, which is impossible in previous works. The proposed method can determine maximum time delay and allowable transmission rate that preserve stability performance of networked control system. The results of the simulation validate effectiveness of our stability analysis method.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.32-35
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• 1996

This paper analyzes characteristics of PMLSM using 3 dimensional equivalent magnetic circuit network method (3-D EMC). PMLSM of which the effective electric-airgap is not only very large, but also the width is finite width lateral edges has much leakage flux. Therefore, 2-D analysis method cannot consider it so carefully that 3-D analysis method must required. 3-D EMC which will be used for analysis of PMLSM performs modeling of it including solt and teeth structure, uses the magnetic motive force of stator winding and permanent magnet as source. and calculates magnetic flux density and force considering nonlinear characteristics of materials. we verified analysis validity by comparing simulation results with expermental results.