• Journal of Magnetics
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• v.15 no.1
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• pp.12-16
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• 2010

Combined study of in-situ stress measurements and atomic force microscopy (AFM) revealed drastic stress relaxation in the CoCrPt and PS(styrene)-PVP(vinyl pyridine) polymer hybrid structure that was closely related to the growth structure of the film. We have observed not only no large initial growth stress at the initial stages of film growth but also twice smaller stress in magnitude with opposite sign in the CoCrPt/PS-PVP/Si sample. The microstructural studies using AFM at the various film growth stages revealed that the film growth structure plays an important role in the stress relaxation mechanism of CoCrPt films on a corrugated polymer surface.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1685-1688
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• 2002

Application Routing Load Balancing (ARLB) is a novel load balancing mode that combines QoS routing and load balancing in per application to support QoS far real-time application based on wired network. Zone Routing Protocol (ZRP) is a recent hybrid proactive/reactive routing approach in an attempt to achieve scalability of ad-hoc network. This routing approach has the potential to be efficient in the generation of control traffic than traditional routing schemes. Up to now, without proper load balancing tools, the ZRP can actually guarantee QoS for delay-sensitive applications when congestion occurred in ad-hoc network. In this paper, we propose the ARLB to improve QoS fur delay-sensitive applications based on ZRP in ad-hoc network when congestion occurred and to be forwarding mechanism fur route coupling to support QoS for real-time applications. The critical point is that the routing metric of ARLB is originally designed for wired network environment. Therefore, we study and present an appropriate metric or cost computation routing of ARLB for recently proposed ZRP over ad-hoc network environment.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2009.11a
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• pp.93-96
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• 2009

The objective of this study is to analyze the insulation characteristics of the polylon hybrid fiber inserted high-strength RC beam and slab produced as a single body and the results of this study can be summarized as follows. In the spalling mechanism as an insulation characteristic, the slab of the single body type specimen shows an exposure in concrete covers at the center of slab and that leads to the spalling, which exposures reinforcing bars. In the case of the beam, the spalling was presented at several sections as a type of peel spalling before and after 10 minutes from the insulation test. Whereas, although the internal temperature history of concrete represents the highest range as 581℃ in the case of the center of the bottom of beam base, it can be considered that it satisfies the regulation of insulation certification.

• Proceedings of the SAREK Conference
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• 2008.11a
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• pp.630-635
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• 2008

A dynamic model has been developed to investigate the operability of a single and double-effect solar energy assisted parallel type absorption chiller. In the study, main components and fluid transport mechanism have been modeled. Flow discharge coefficients of the valves and the pumps were optimized for the double-effect mode with solar-heated water circulated. The model was run for the single mode with solar energy supply only and the solar/gas driving double effect mode. And the cases of the double mode with and without the solar energy were compared. From the simulation results, it was found that the present configuration of the chiller is not capable of regulating solution flow rates according to variable solar energy input. And the single mode utilizing the solar energy only is not practical. It is suggested to operate the system in the double mode and the flow rate control system adaptive to variable solar energy input has to be developed.

• Industrial Engineering and Management Systems
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• v.11 no.4
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• pp.310-330
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• 2012

Scheduling is an important tool for a manufacturing system, where it can have a major impact on the productivity of a production process. In manufacturing systems, the purpose of scheduling is to minimize the production time and costs, by assigning a production facility when to make, with which staff, and on which equipment. Production scheduling aims to maximize the efficiency of the operation and reduce the costs. In order to find an optimal solution to manufacturing scheduling problems, it attempts to solve complex combinatorial optimization problems. Unfortunately, most of them fall into the class of NP-hard combinatorial problems. Genetic algorithm (GA) is one of the generic population-based metaheuristic optimization algorithms and the best one for finding a satisfactory solution in an acceptable time for the NP-hard scheduling problems. GA is the most popular type of evolutionary algorithm. In this survey paper, we address firstly multiobjective hybrid GA combined with adaptive fuzzy logic controller which gives fitness assignment mechanism and performance measures for solving multiple objective optimization problems, and four crucial issues in the manufacturing scheduling including a mathematical model, GA-based solution method and case study in flexible job-shop scheduling problem (fJSP), automatic guided vehicle (AGV) dispatching models in flexible manufacturing system (FMS) combined with priority-based GA, recent advanced planning and scheduling (APS) models and integrated systems for manufacturing.

• Journal of Intelligence and Information Systems
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• v.9 no.3
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• pp.99-115
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• 2003

In this paper, we present a knowledge-based object-oriented spatial database system called KOBOS. A knowledge-based approach is introduced to the object-oriented spatial database system for data modeling and approximate query answering. For handling the structure of spatial objects and the approximate spatial operators, we propose three levels of object-oriented data model: (1) a spatial shape model; (2) a spatial object model; (3) an internal description model. We use spatial type abstraction hierarchies(STAHs) to provide the range of the approximate spatial operators. We then propose SOQL, a spatial object-oriented query language. SOQL provides an integrated mechanism for the graphical display of spatial objects and the retrieval of spatial and aspatial objects. To support an efficient hybrid query evaluation, we use the top-down spatial query processing method.

• Proceedings of the KIEE Conference
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• summer
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• pp.1251-1253
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• 2004

This paper is proposed a fuzzy neural network controller based on the vector controlled surface permanent magnet synchronous motor(SPMSM) drive system. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of SPMSM using neuro-fuzzy control(NFC) and estimation of speed using artificial neural network(ANN) Controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new method.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.420-423
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• 2009

The conventional fixed gain PI controller is very sensitive to step change of command speed, parameter variation and load disturbances. The precise speed control of interior permanent magnet synchronous motor(IPMSM) drive becomes a complex issue due to nonlinear coupling among its winding currents and the rotor speed as well as the nonlinear electromagnetic developed torque. Therefore, there exists a need to tune the PI controller parameters on-line to ensure optimum drive performance over a wide range of operating conditions. This paper is proposed hybrid intelligent-PI(HIPI) controller of IPMSM drive using adaptive learning mechanism(ALM) and fuzzy neural network(FNN). The proposed controller is developed to ensure accurate speed control of IPMSM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. The PI controller parameters are optimized by ALM-FNN at all possible operating condition in a closed loop vector control scheme. The validity of the proposed controller is verified by results at different dynamic operating conditions.

• Journal of Microbiology
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• v.41 no.4
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• pp.295-299
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• 2003

Adenovirus (Ad) precursor to the terminal protein (pTP) plays an essential roles in the viral DNA replication. Ad pTP serves as a primer for the synthesis of a new DNA strand during the initiation step of replication. In addition, Ad pTP forms organized spherical replication foci on the nuclear matrix (NM) and anchors the viral genome to the NM. Here we identified the interferon inducible gene product 1-8D (Inid) as a pTP binding protein by using a two-hybrid screen of a HeLa cDNA library. Of the clones obtained in this assay, nine were identical to the Inid, a 13-kDa polypeptide that shares homology with genes 1-8U and Leu-13/9-27, most of which have little known functions. The entire open reading frame (ORF) of Inid was cloned into the tetracycline inducible expression vector in order to determine the biological functions related with adenoviral infection. When Inid was introduced to the cells along with adenoviruses, fifty to sixty percent of Ad-infected cells expressing Inid had rounded morphology, which was suggestive of apoptosis. Results from the terminal deoxynucleotidyl transferase (TdT) and DNA fragmentation assays confirmed that Inid induces apoptosis in Ad-infected or in uninfected cells. The Inid binding to pTP may target the cell for apoptotic destruction as a host defense mechanism against the viral infection.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.2
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• pp.127-136
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• 2005

In this paper, a new architecture and comprehensive design methodology of genetically optimized Rule-based Fuzzy Polynomial Neural Networks(gRFPNN) are introduced and a series of numeric experiments are carried out. The architecture of the resulting gRFPNN results from asynergistic usage of the hybrid system generated by combining rule-based Fuzzy Neural Networks(FNN) with polynomial neural networks (PNN). FNN contributes to the formation of the premise part of the overall rule-based structure of the gRFPNN. The consequence part of the gRFPNN is designed using PNNs. At the premise part of the gRFPNN, FNN exploits fuzzy set based approach designed by using space partitioning in terms of individual variables and comes in two fuzzy inference forms: simplified and linear. As the consequence part of the gRFPNN, the development of the genetically optimized PNN dwells on two general optimization mechanism: the structural optimization is realized via GAs whereas in case of the parametric optimization we proceed with a standard least square method-based learning. To evaluate the performance of the gRFPNN, the models are experimented with the use of several representative numerical examples. A comparative analysis shows that the proposed gRFPNN are models with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.