• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.472-472
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• 2009

The safety of cultural properties, medical treatment and electrical communication equipments in a building was hardly considered against the earthquake induced vibration, while the integrity of the building structure has been taken into account through the resistant earthquake design. This paper presents design of a seismic isolation table for both indoor and outdoor electrical communication equipment. First of all, artificial earthquake waves compatible with floor and ground response spectra for electrical communication equipments are generated using previously recorded seismic waves. Two kinds of one-degree-of-freedom seismic isolation table systems: spring-linear damper and spring-friction damper systems are considered and their responses to artificial earthquake waves are simulated. Design parameter study for two seismic isolation tables are performed through simulations and a seismic isolation table for both indoor and outdoor electrical communication equipment is designed considering the simulation results.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.323-335
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• 1999

In this paper, we propose a new hybrid model of artificial neural networks(ANNs) and genetic algorithm (GA) to optimal feature transformation and feature weighting. Previous research proposed several variants of hybrid ANNs and GA models including feature weighting, feature subset selection and network structure optimization. Among the vast majority of these studies, however, ANNs did not learn the patterns of data well, because they employed GA for simple use. In this study, we incorporate GA in a simultaneous manner to improve the learning and generalization ability of ANNs. In this study, GA plays role to optimize feature weighting and feature transformation simultaneously. Globally optimized feature weighting overcome the well-known limitations of gradient descent algorithm and globally optimized feature transformation also reduce the dimensionality of the feature space and eliminate irrelevant factors in modeling ANNs. By this procedure, we can improve the performance and enhance the generalisability of ANNs.

• Structural Engineering and Mechanics
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• v.16 no.5
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• pp.581-595
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• 2003

Since the conventional direct approaches are hard to be applied for damage diagnosis of complex large-scale structures, a two-step approach for diagnosing the joint damage of framed structures is presented in this paper by using artificial neural networks. The first step is to judge the damaged areas of a structure, which is divided into several sub-areas, using probabilistic neural networks with natural Frequencies Shift Ratio inputs. The next step is to diagnose the exact damage locations and extents by using the Radial Basis Function (RBF) neural network with the second Element End Strain Mode of the damaged sub-area input. The results of numerical simulation show that the proposed approach could diagnose the joint damage of framed structures induced by earthquake action effectively and has reliable anti-jamming abilities.

• Journal of Electrical Engineering and Technology
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• v.6 no.6
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• pp.760-768
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• 2011

The performance of transmission lines and its shielding design during a lightning phenomenon are quite essential in the maintenance of a reliable power supply to consumers. The leader progression model, as an advanced approach, has been recently developed to calculate the shielding failure rate (SFR) of transmission lines using geometrical data and physical behavior of upward and downward lightning leaders. However, such method is quite time consuming. In the present paper, an effective method that utilizes artificial neural networks (ANNs) to create a metamodel for calculating the SFR of a transmission line based on shielding angle and height is introduced. The results of investigations on a real case study reveal that, through proper selection of an ANN structure and good training, the ANN prediction is very close to the result of the detailed simulation, whereas the Processing time is by far lower than that of the detailed model.

• Proceedings of the Materials Research Society of Korea Conference
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• 2011.05a
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• pp.54.1-54.1
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• 2011

Porous hydroxyapatite has been widely used as clinical implanted material. However, it has poor mechanical properties. To increase the strength as well as the biocompatibility of the porous HAp based artificial bone, it was fabricated by multi-extrusion process. Hydroxyapatite and graphite powders were mixed separately with ethylene vinely acetate and steric acid by shear mixing process. Hydroxyapatite composites containing porous microstructure were fabricated by arranging it in the die and subject it to extrusion process. Burn-out and sintering processes were performed to remove the binder and graphite as well as increase the density. The external and internal diameter of cylindrical hollow core were approximately 10.4 mm and 4.2 mm, respectively. The size of pore channel designed to increase bone growth (osteconduction) was around 150 ${\mu}m$ in diameter. X-ray diffraction analysis and SEM observation were performed to identity the crystal structure and the detailed microstructure, respectively.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.2
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• pp.35-44
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• 1998

This paper describes multiple fault diagnosis method in complex system with hierarchical structure. Complex system is divided into subsystem, item and component. For diagnosing this hierarchical complex system, it is necessary to implement special neural network. We introduced Modular Artificial Neural Network(MANN) for this purpose. MANN consists of four level neural network, first level for symptom classification, second level for item fault diagnosis, third level for component symptom classification, forth level for component fault diagnosis. Each network is multi layer perceptron with 7 inputs, 30 hidden node and 7 outputs trained by backpropagation. UNIX IPC(Inter Process Communication) is used for implementing MANN with multitasking and message transfer between processes in SUN workstation. We tested MANN in reactor system.

• Journal of Advanced Marine Engineering and Technology
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• v.34 no.7
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• pp.971-980
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• 2010

In this paper, an artificial neural network (ANN) was employed to build a predicting model for refrigerator structure. The predicting model includes three input variables of the plaque depth (D), width (W) and interval distance(S) on the inner wall. Finite element method was utilized to obtain the data, which would be necessary for the ANN training process. Finally, a genetic algorithm (GA) was applied to find the optimal parameters that leaded to the minimum inner case deformation under operating condition. The optimal combination found is the depth(D) of 2.63mm, the width(W) of 19.24mm and the interval distance(S) of 49.38mm which leaded to the smallest deformation of 1.88mm for the given refrigerator model.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.2107-2112
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• 2010

To analyze the effect of temperature on pavement types of dedicated lane, we have performed a temperature monitoring for pavements which were constructed in test track for Bimodal Tram. These pavements classified into four types; natural and artificial lawn, concrete and asphalt. Dedicated lane composed of natural and artificial lawn has a complex structure with concrete slab in contact surface of tires, and with 1m natural or artificial lawn in the middle part of lane. From monitoring results for pavements, dedicated lane with natural lawn shows lower temperature value compared with other dedicated lanes, and it is expected to decrease the heat island effect of conventional road if constructed.

• International Journal of Contents
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• v.15 no.4
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• pp.107-112
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• 2019

With the development of AI (artificial intelligence), animation digital publishing has been integrated with intellectualization. This paper adopts the theory of the global value chain, and analyzes the basic structure of the animation publishing value chain. Then focuses on the analysis of digital technology and artificial intelligence technology to play an active role in the topic selection and content customization of animation digital publishing products, optimization of publishing platforms, and user experience of publishing products. Finally, it proposes the use of artificial intelligence data analysis and deep learning technology. The purpose of this paper is to realize the upgrading of animation digital publishing, product upgrading, industrial chain upgrading, and identify some promotion methods for the value chain, such as copyright protection.

• Journal of Life Science
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• v.9 no.1
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• pp.17-21
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• 1999

Chitosan derivitives, a sulfated N-acetylchitosan was synthesized, and artificial skin of sulfated N-acetylchitosan and N-carboxyl butyl chitosan were investigated. Sulfated derivatives of chitosan were analyzed by {TEX}${13}^C${/TEX}-NMR and the structure on N-acetyl chitosan 3,6-O-disulfate were confirmed. Rabbits underwent a midline laparotomy followed either by a bilateral peritoneal sidewall abraison(3.0×1.5cm). The injured surface was then covered with 0.2mm thick sulfated N-acetyl chitosan membrane. Sulfated N-acetyl chitosan membrane was found to reduce postsurgical bleeding after abraison of peritoneal surface treated with sulfated N-acetyl chitosan membrane. Sulfated N-acetyl chitosan implanted rabbit showed quick wound healing than N-carboxybutyl chitosan. With a sterilization procedure of chemical sterilization, sulfated N-acetyl chitosan seem to be better substitutes than N-carboxybutyl chitosan.