• Tunnel and Underground Space
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• v.6 no.1
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• pp.30-38
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• 1996

A two dimensional analysis program for groundwater flow in fractured network was developed to analyze the influence of discontinuity characteristics on groundwater flow. This program involves the generation of discontinuities and also connectivity analysis. The discontinuities were generated by the probabilistic density function(P.D.F.) reflecting the characteristics of discontinuities. And the fracture network model was completed through the connectivity analysis. This program also involves the analysis of groundwater flow through the discontinuity network. The result of numerical experiment shows that the equivalent hydraulic conductivity increased and became closer to isotropic as the density and trace length increased. And hydraulic head decreased along the fracture zone because of much water-flow. The grouting increased the groundwater head around cavern. An analysis of groundwater flow through discontinuity network was performed around underground oil storage cavern which is now under construction. The probabilistic density functions(P.D.F) were obtained from the investigation of the discontinuity trace map. When the anisotropic hydraulic conductivity is used, the flow rate into the cavern was below the acceptable value to maintain the hydraulic containment. But when the isotropic hydraulic conductivity is used, the flow rate was above the acceptable value.

• Journal of the Semiconductor & Display Technology
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• v.21 no.3
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• pp.130-134
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• 2022

An anti-reflective coating is used to improve the performance of the solar cell. The anti-reflective coating changes the value of the short-circuit current about the thickness. However, the current-voltage characteristics about the anti-reflective coating are difficult to calculate without simulation tool. In this paper, a modeling technique to determine the short-circuit current value and the current-voltage characteristics in accordance with the thickness is proposed. In addition, artificial neural network is used to predict the short-circuit current with the dependence of temperature and thickness. Simulation results incorporating the artificial neural network model are obtained using MATLAB/Simulink and show the current-voltage characteristic according to the thickness of the anti-reflective coating.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.2
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• pp.106-117
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• 2022

Multiple output converters can be utilized when various output voltages are required in applications. Recently, one of the multiple output converters called fly-buck has been proposed, and has attracted attention due to the advantage that multiple output can be easily obtained with a simple structure. When constant on-time (COT) control is applied, the output ripple voltage must be treated carefully for control stability and voltage regulation characteristics in consideration of the inherent energy transfer characteristics of the fly-buck converter. This study analyzes the operation principle of the fly-buck converter with a ripple generation network and presents the design guideline for the improved output voltage regulation. Validity of the analysis and design guideline is verified using a 5 W prototype of the COT controlled fly-buck converter with a ripple generation network for telecommunication auxiliary power supply.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.4
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• pp.110-118
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• 1997

Multi-layer neural networks with error back-propagation algorithm have a great potential for identifying nonlinear systems with unknown characteristics. However, because they have a demerit that the speed of convergence is too slow, various methods for improving the training characteristics of backpropagition networks have been proposed. In this paper, a fuzzy division method is proposed to improve the convergence speed, which can find out an effective fuzzy division by the tuning of membership function and independently train each neural network after dividing the network model into several parts. In the simulations, the proposed method showed that the optimal fuzzy partitions could be found from the arbitray initial ones and that the convergence speed was faster than the traditional method without the fuzzy division.

• Journal of Digital Convergence
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• v.15 no.9
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• pp.415-425
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• 2017

The purpose of this study is to examine the effect of perceived enjoyment and user's characteristics on the intention of continuous use when users play social network games on a mobile device. In addition, the study empirically investigated the mediating effect of flow experience in this process. To fulfill the purpose, this study conducted a survey on 244 college students and collected data. When the collected data was analyzed, the followings were known. First, perceived enjoyment, and both self-efficacy and innovation propensity of user's characteristics turned out to have a positive (+) effect on the intention of continuous use in mobile social network game. Second, in the process, it was known that flow experience played a mediating role. These findings are expected to be useful data in developing game contents of high quality or making a marketing strategy for continuous improvement of online social network game industry. In addition, future studies are expected to generalize the research to various age groups.

• Knowledge Management Research
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• v.24 no.4
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• pp.177-193
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• 2023

This study explores the role of organizational culture, job characteristics, and work values and orientation in shaping the competitiveness of a multinational company (MNC) based in Korea. The purpose of the study was to examine the impact of these variables on the competitiveness attributes of the organizational culture profile through MR-QAP analysis. Data were collected from 161 employees in 15 different teams at a Korean automotive company headquartered in Seoul. The results of the study revealed the impact of network characteristics associated with competitive organizational culture on competitiveness. 'found to have a negative effect on competitiveness. Among the organizational culture profiles, social responsibility, supportiveness, innovation, and performance orientation have a significant positive effect on competitive organizational culture, while emphasis on rewards and stability have no significant effect. These findings provide practical implications for understanding the complex dynamics of organizational culture and promoting strategic approaches to enhance organizational competitiveness.

• Design & Manufacturing
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• v.17 no.4
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• pp.72-78
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• 2023

Injection molding is a process widely used in various industries because of its high production speed and ease of mass production during the plastic manufacturing process, and the product is molded by injecting molten plastic into the mold at high speed and pressure. Since process conditions such as resin and mold temperature mutually affect the process and the quality of the molded product, it is difficult to accurately predict quality through mathematical or statistical methods. Recently, studies to predict the quality of injection molded products by applying artificial neural networks, which are known to be very useful for analyzing nonlinear types of problems, are actively underway. In this study, structural optimization of neural networks was conducted by applying multi-task learning techniques according to the characteristics of the input and output parameters of the artificial neural network. A structure reflecting the characteristics of each process step was applied to the input parameters, and a structure reflecting the quality characteristics of the injection molded part was applied to the output parameters using multi-tasking learning. Building an artificial neural network to predict the three qualities (mass, diameter, height) of injection-molded product under six process conditions (melt temperature, mold temperature, injection speed, packing pressure, pacing time, cooling time) and comparing its performance with the existing neural network, we observed enhancements in prediction accuracy for mass, diameter, and height by approximately 69.38%, 24.87%, and 39.87%, respectively.

• Information Systems Review
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• v.17 no.2
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• pp.179-192
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• 2015

Collaborative research has been actively done on the basis of academic relationships among various study area. The importance of collaboration has also been increased. Collaborative researchers can reduce time, cost, and research risk to maximize research productivity. This study aims to develop a framework for understanding the behavior of professional groups through network characteristics. To achieve the goal, we collected data of the co-authored network and that of the reviewer network from from 2006 to 2012. Total 230 submitted papers were analyzed on the views of research performance and productivity. Various analytical methods such as centrality analysis, sub-group analysis, correlation, and regression were conducted for assuring the reliability and validity of our research. The results shows that the productivity of the co-authored network was increased and the efficiency of the reviewer network was also identified through several network indexes.

• Korean Journal of Acupuncture
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• v.29 no.3
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• pp.431-440
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• 2012

Objectives : Recently, network science is very popular topic in various scientific fields and many studies have reported that it gives meaningful results on studying characteristics of a complex system. In this study, based on network theory, we made acupoints network using data of combined acupoints which appeared at "Beijiqianjinyaofang". We focused to find out the distinctive roles of remote and local combinations on the network. Furthermore, we aimed to identify the possibility of numerical and quantitative application to acupuncture researches. Methods : Based on examples of combined acupoints in "Beijiqianjinyaofang", the network consisted of 291 nodes and 2,431 links. The spatial distances between combined acupoints were calculated by the human dummy model. We removed the links step by step for the three cases - remote, local, and random cases, and observed the characteristic changes by calculating path lengths, similarity indices, and clustering coefficients. Also cluster analysis was carried out. Results : The network had a small number of remote links, and a large number of local links. These two links had the distinct characteristics. Whereas the local links formed a cluster of nearby nodes, remote links played a role to increase the correlation between the clusters. Conclusions : These results suggest that acupoints network increases the connectivity between the distal part and the trunk of human body, and enables various combinations of the acupoints. This finding conclusively showed that mechanism of combined acupoints could be interpreted meaningfully by applying network theory in acupuncture researches.

• Journal of Korea Multimedia Society
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• v.12 no.1
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• pp.139-146
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• 2009

This paper deals with visualization that can appropriately show the characteristics deduced from relationships between pieces of information. The visualization of influence, which is used as an important index in deducing the characteristics of relationships in social network analysis, was selected as research topic, and first, the elements that show relationships within the network and the index that show influence were classified and organized. Second, the links between relational elements that show influence in social network were examined, and an influence visualization network was created. Third, an influence visualization framework was proposed which explains the interaction between social network analysis and visualization process. The influence visualization network and framework being proposed in this paper can be used not only to understand and analyze the elements that influence social network but also to make it possible to have a rational and efficient approach to network visualization. Hopefully, they will become a new methodological approach to information design.