• Journal of Korean Institute of Industrial Engineers
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• v.37 no.4
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• pp.279-288
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• 2011

The past researches focused on the supply chain network that consists of factories, distribution centers and retailers for single product type. This research is required because the factory for single product type is advanced to reconfigurable type in order to produce various products, according to customers' various purchase forms and time. This research is also required because in the past researches, the material flows from factories to distribution centers and from distribution centers to retailers, but recently, there are material flows between distribution centers. The supply chain network in this research consists of reconfigurable manufacturing system, multi-layered distribution centers, and retailers. A simulator is developed to analyze the material flow on the supply chain network. The developed simulator is web-based designed by using Java Server Page and MS-SQL, so as to maximize the convenience for users.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.86-86
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• 2000

This paper describes a neural network based fuzzy type PID control scheme. The PID controller is being widely used in industrial applications. however, it is difficult to determine the appropriate PID gains for (he nonlinear system control. In this paper, we re-analyzed the fuzzy controller as conventional PID controller structure, and proposed a neural network based fuzzy type PID controller whose scaling factors were adjusted automatically. The value of initial scaling factors of the proposed controller were determined on the basis of the conventional PID controller parameters tuning methods and then they were adjusted by using neural network control techniques. Proposed controller was simple in structure and computational burden was small so that on-line adaptation was easy to apply to. The result of practical experiment on the magnetic levitation system, which is known to be hard nonlinear, showed the proposed controller's excellent performance.

• The Journal of the Acoustical Society of Korea
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• v.13 no.4
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• pp.5-11
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• 1994

In this paper, the ciassification of Korean character type using multi neural network and fuzzy inference based on block partition is studied. For the effective classification of a consonant and a vowel, block partition method which devide the region of a consonant and a vowel for each type in the character is proposed. And the partitioned block can be changed according to the each type adaptively. For the improvement of classification rate, the multi neural network with a whole and a part neural network is consisted, and the character type by using fuzzy inference is decided. To verify the validity of the proposed method, computer simulation is accomplished, and from the classification rate $92.6\%$, the effectivity of the method is confirmed.

• The Journal of Information Systems
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• v.32 no.3
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• pp.41-61
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• 2023

Purpose This study aims to categorize the types of health, analyze the effects among health types based on network analysis find the most important type of health, and explain whether the results between health types vary depending on demographic characteristics. Design/methodology/approach This study investigated individual physical, clinical, mental, and social health(social capital and social support) levels through a survey of 100 people. Network analysis was applied to the survey data to confirm the degree centrality of nodes. Furthemore, we investigated the differences in core nodes according to gender and age groups. Findings According to the analysis result, social support was the most important health type in the entire group. Furthermore, the importance of health type was different depending on the characteristics of the groups. In the case of men, clinical health was the most important health type, and social support was analyzed to be the most important for women. In the case of young people, clinical health was the most important health type, and mental health was the most important health type in the middle-aged.

• Korean Journal of Social Welfare
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• v.43
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• pp.7-41
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• 2000

This study attempted to identify the type of social network interventions and barriers to implement them. Few empirical studies have been conducted concerning social network interventions as professional activities. Although social support and social network interventions have been noted as important practice concepts, the existing studies ten us little about how social workers perceive and experience social network interventions. This study used seven types of social network interventions identified in the previous studies. And based on "obstacles to social network interventions scale" developed by Biegel, Tracy & Song (1995), a twenty-two item scale was developed by the authors. The results from this study show that social workers little implement social network interventions such as community empowerment, family caregiver enhancement, and support group, and that they perceive organization characteristics and profession-oriented culture as important obstacles to implement social network interventions. The findings from this study suggest various strategies to address these barriers.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.37-42
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• 2007

A network of MAC type was constructed in the Gyeonggi-do area to analyze the usefulness and validity of the Network RTK-GPS. Six sites were selected to conduct GPS observation for 24 hours, and by determining the ITRF of each site, coordinates were determined in connection with IGS network. Then check points which were established in Gimpo area were observed at least 7 times by Network RTK at 20 secs of retrieval intervals. The result showed high accuracy in the difference between the coordinates determined immediately by the in-field network survey and the current performance was 1-2cm. Its biggest benefit is the expanded range of survey and efficiency of practice. In summary, it is proved that a network survey has the accuracy, scalability and efficiency and it is expected that the network survey will contribute to the cadastral survey.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.6
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• pp.24-33
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• 2011

This paper describes a gateway system based on a MOST network for integrating several different automotive network protocols. For transparent data communication among different protocols regardless of the high-level messages and the data format, Pseudo MOST frame was designed based on MOST frame and this pseudo MOST data frame is used as the data carrier. For automotive application, two types of gateways were developed, one board-type gateway and small-sized module-type gateways. One board-type gateway has ethernet port, video port and audio port. Meanwhile, small-sized module-type gateways are developed for video, audio, bluetooth and Flexray, respectively. Experiments with a network system using several small-sized module gateways verified efficient data communication among different network protocols and confirmed the effectiveness of the proposed gateway system for automotive network integration.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.16 no.5
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• pp.198-202
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• 2006

We could achieve the bridge-type formation of the iridium-catalyzed carbon nanofibers across the gap on the MgO substrate using microwave plasma enhanced chemical vapor deposition method. On the plane surface area of the MgO substrate, the iridium-catalyzed carbon nanofibers were grown as a lateral direction to the substrate. The bridge-type formation and/or the lateral growth of the iridium-catalyzed carbon nanofibers were interconnected with each other. Finally, they could form an entangled network having the bridge-type formation of the carbon nanofibers across the gap on the substrate and the laterally-grown carbon nanofibers on the plane surface area of the substrate. The entangled network showed the semiconductor electrical characteristics.

• Proceedings of the KIEE Conference
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• summer
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• pp.384-387
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• 2004

The direction and the type of a fault on a transmission line need to be identified rapidly and correctly, The work described in this paper addresses the problem encountered by a conventional algorithm in a fault type classification in double circuit line, this arises due to a mutual coupling and CT saturation under the fault condition. We present an approach to identify fault type with novel neural network on double circuit transmission line. The neural network based on combined unsupervised training method provides the ability classify the fault type by different patterns of the associated voltages and currents.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.238-243
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• 2007

The TAM(Topographic Attentive Mapping) network neural network model is an especially effective one for pattern analysis. It is composed of of Input layer, category layer, and output layer. Fuzzy rule, lot input and output data are acquired from it. The TAM network with three pruning rules for reducing links and nodes at the layer is called fuzzy TAM network. In this paper, we apply fuzzy TAM network to pattern analysis of leadership type for organizational leader and show its usefulness. Here, criteria of input layer and target value of output layer are the value and leadership related personality type variables of the Egogram and Enneagram, respectively.