• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.10a
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• pp.96-101
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• 2000

In this paper, we have proposed a new approach to the design of robot vision system to develop the technology for the automatic test and assembling of precision mechanical and electronic parts for the factory automation. In order to perform real time implementation of the automatic assembling tasks in the complex processes, we have developed an intelligent control algorithm based-on neural networks control theory to enhance the precise motion control. Implementing of the automatic test tasks has been performed by the real-time vision algorithm based-on TMS320C31 DSPs. It distinguishes correctly the difference between the acceptable and unacceptable defective item through pattern recognition of parts by the developed vision algorithm. Finally, the performance of proposed robot vision system has been illustrated by experiment for the similar model of fifth cell among the twelve cell for automatic test and assembling in S company.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1183-1188
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• 2004

The inverse heat conduction problem (IHCP) is a problem of estimating boundary condition from temperature measurement at one or more interior points. Neural networks are general information processing systems inspired by the connectionist theory of human brain. By properly training the network by the learning rule, the neural network method can handle many non-linear or other complex problems. In this work, neural network is applied to complicated inverse heat conduction problems. Efficiency of the procedure is enhanced by incorporating the radial basis functions (RBF). The RBF is trained faster than other neural network and can find smooth solution. In order to demonstrate the effectiveness of the current scheme, a typical one-dimensional IHCP is considered. At one surface, the temperature as well as the heat flux is known. The unknown temperature of interest is estimated on the other side of the slab. The results from the proposed method based on RBF neural network are compared with the conventional method.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.52-57
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• 2011

Bridges are essential and valuable elements in road and rail transportation networks. Bridge remediation is a top priority for asset managers, but identifying the nature of true defect deterioration and associated remediation treatments remains a complex task. Nowadays Decision Support Systems (DSS) are used extensively to assist in decision-making across a wide spectrum of unstructured decision environments. In this paper a requirements-driven framework is used to develop a risk based decision support model which has the ability to quantify the bridge condition and find the best remediation treatments using Multi Attribute Utility Theory (MAUT), with the aim of maintaining a bridge within acceptable limits of safety, serviceability and sustainability.

• Journal of the Korean Geographical Society
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• v.48 no.3
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• pp.366-386
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• 2013

This paper analyzes the drought and restriction on water supply in Taebaek City during the winter season in 2008 using Actor-Network Theory. Actor-Network Theory emphasizes and brings into view the role and act of non-human actors as well as human actors in various environmental issues. The fact that only Taebaek experienced restriction on water supply for 88 days although the winter season drought in 2008 affected the whole nation, requires a synthetic analysis of both human and non-human actors and their relationships and networks embedded in Taebaek City at that time. This paper shows that both human and non-human actors including Taebaek City Hall, Korea Water Resource Corporation, Taebaek citizen, the water supply facilities, Gwangdongdam, obsolete water pipes, the topography of Taebaek, soil, the change of industry, and population interact one another transforming the geography of water in Taebaek. This study helps to understand the complex processes related to drought disasters at a specific local scale and to provide appropriate measures to drought.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.7
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• pp.421-428
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• 2006

In this paper, the way of remote installation and back-up of 3-tier structure is introduced for efficient utilizing the cluster system resources distributed at several places. Recently, cluster system is constructed as the system of over hundreds nodes under complex network system mixed with public networks and private networks. Therefore, the as installation method suitable for the large scale cluster system and the remote recovery of failure nodes are important. However the previous researches which are based on 2-tier architecture may not provide the efficient cluster installation and image back-up method when the network of cluster system is composed of several private networks and public networks. In this paper, RISE (Remote Installation Service and Environment) based on the 3-tier architecture is proposed to solve this problem. In our approach, the managing node's role is divided into the global master node (GRISE) and the local master node (LRISE) to provide the efficient initial system deployment and remote failure recovery of distributed cluster system under the various network systems. Also, LRISE's availability is ensured under the complex network environments by adopting the auto-synchronization mechanism between GRISE and LRISE. In this work, a 64-node cluster system with gigabit network system is utilized for the experiment. From the experimental result, the system image with 1.86GB data can be obtained in 5 minutes and 53 seconds and the image-based installation of 64-node system can be carried out in 17 minutes and 53 seconds.

• International Commerce and Information Review
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• v.14 no.2
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• pp.249-269
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• 2012

The focus of our work is to identify and understand the drivers of alliance performance so that businesses can maximize their chances of a successful alliance-an area that has received little attention in empirical modeling. Although both conceptual and applied research on alliances has increased, an empirically tested comprehensive theoretical model that explains alliance performance has yet to be developed. Using five salient perspective, namely market power theory, transaction cost theory, the resource-based view, institutional theory, real option theory, this paper attempts to provide a theoretical rationale linking motives of global alliance networks on firm's capabilities, partner's capabilities, operating structures, and performances of Korean companies. The key contribution of this study is that it paints a picture of what matters in driving alliance performance. Our work shows the complex nature of driving performance and the interplay of firm's capabilities, partner's capabilities, and operating structures for understanding alliance performances. This study has given us a small but significant step forward towards understanding the intricacies of alliance performance. We are now better able to understand the respective roles played by various alliance factors and derive insights that lead to improved alliance performance.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2005.04a
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• pp.663-671
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• 2005

Distributed operation of overall structural design process, by which product and process optimization are implemented, is presented in this paper. The database-interconnected multilevel hybrid method, in which the conventional design method and the optimal design approach are combined, is utilized there. The method selectively takes the accustomed procedure of the conventional method in the conceptional framework of the optimal design. Design conditions are divided into primary and secondary criteria This staged application of design conditions reduces the computational burden for large complex optimization problems. Two kinds of numeric and graphic processes, are simultaneously implemented on the basis of concurrent engineering concepts in the distributed environment of PC networks. Numerical computation on server and graphic works on independent client are communicated through message passing. Numerical design is based on the optimization methodology and the drawing process is carried out by AutoCAD using the AutoLISP programming language. The prototype design experimentation for some steel trusses shows the validity and usability of the method. This study has sufficient adaptability and expandability in methodology, in that it is based on general theory and industry standard systems.

• Smart Structures and Systems
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• v.15 no.4
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• pp.1139-1158
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• 2015

This paper proposes an efficient system identification method for modeling nonlinear behavior of civil structures. This method is developed by integrating three different methodologies: principal component analysis (PCA), artificial neural networks, and fuzzy logic theory, hence named PANFIS (PCA-based adaptive neuro-fuzzy inference system). To evaluate this model, a 3-story building equipped with a magnetorheological (MR) damper subjected to a variety of earthquakes is investigated. To train the input-output function of the PANFIS model, an artificial earthquake is generated that contains a variety of characteristics of recorded earthquakes. The trained model is also validated using the1940 El-Centro, Kobe, Northridge, and Hachinohe earthquakes. The adaptive neuro-fuzzy inference system (ANFIS) is used as a baseline. It is demonstrated from the training and validation processes that the proposed PANFIS model is effective in modeling complex behavior of the smart building. It is also shown that the proposed PANFIS produces similar performance with the benchmark ANFIS model with significant reduction of computational loads.

• Journal of the Optical Society of Korea
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• v.20 no.6
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• pp.704-715
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• 2016

In this paper, we explore a low-complex bandwidth allocation (BA) scheme with multi-level service guarantees in VLC-OFDM systems. Effective capacity theory, which evaluates wireless channel capacity from a novel view, is utilized to model the system capacity under delay QoS constraints of the link layer. Since intensity modulation of light is used in the system, problems caused by frequency selectivity can be neglected. Then, the BA problem can be formulated as an integer programming problem and it is further relaxed and transformed into a concave one. Lagrangian formulation is used to reformulate the concave problem. Considering the inefficiency of traditional gradient-based schemes and the demand for distributed implementation in local area networks, we localize the global parameters and propose a quasi-distributed quadratic allocation algorithm to provide two-level service guarantees, the first level is QoS oriented, and the second level is QoE oriented. Simulations have shown the efficient performance of the proposed algorithm. The users with more stringent QoS requirements require more subcarriers to guarantee their statistical delay QoS requirements. We also analyze the effect of subcarrier granularity on the aggregate effective capacity via simulations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.4
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• pp.730-737
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• 2001

In this paper, an stabilization control method using adaptive neuro-fuzzy controller(ANFC) is proposed for modeling of nonlinear complex systems. The proposed adaptive neuro-fuzzy controller implements system structure and parameter identification using the intelligent schemes together with optimization theory, linguistic fuzzy implication rules, and neural networks from input and output data of processes. The results show that the proposed method can produce the intelligence model with higher accuracy than other works achieved previously.