• Earthquakes and Structures
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• v.10 no.4
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• pp.757-768
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• 2016

In the past decades, effect of near field earthquake on the historical monuments has attracted the attention of researchers. So, many analyses in this regard have been presented. Tunnels as vital arteries play an important role in management after the earthquake crisis. However, digging tunnels and seismic effects of earthquake on the historical monuments have always been a challenge between engineers and historical supporters. So, in a case study, effect of near field earthquake on the historical monument was investigated. For this research, Finite Element Analysis (FEM) in soil environment and soil-structure interaction was used. In Plaxis 2D software, different accelerograms of near field earthquake were applied to the geometric definition. Analysis validations were performed based on the previous numerical studies. Creating a nonlinear relationship with space parameter, time, angular and numerical model outputs was of practical and critical importance. Hence, artificial Neural Network (ANN) was used and two linear layers and Tansig function were considered. Accuracy of the results was approved by the appropriate statistical test. Results of the study showed that buildings near and far from the tunnel had a special seismic behavior. Scattering of seismic waves on the underground tunnels on the adjacent buildings was influenced by their distance from the tunnel. Finally, a static test expressed optimal convergence of neural network and Plaxis.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.21 no.10
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• pp.537-544
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• 2009

On account of the technological development, intelligent building is on increasing where the artificial regulation on indoor environment is possible, thence the concern about those facilities such as water-supply facility, water-heater and drainage facility has becomes higher. However, due to diversification and complicated system of the facility-equipments, the noise generating from such facility equipment is gradually becoming a problem, and since especially equipment noises arising at the machine room frequently infringe into the resident's pleasant living environment with the complex types of an air-borne sound and a structure-borne sound, it is becoming the civil complaint. On such viewpoint, this Study ever observed the characteristics of noise generating from various facility-equipments in the building, and intended to evaluate the facility-noises by use of the valuation index such as PSIL, N, NC, NR. As result of, the facilities noise which happens in the machine room makes normal conversation very difficult due to high sound pressure level. Based on such data, this study is willing to present it as an essential material for establishment an efficient measure against the facility-noises arising at machine room hereafter.

• Korean Journal Plant Pathology
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• v.14 no.5
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• pp.413-417
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• 1998

Magnaporthe grisea, the casual agent of rice blast, requires formation of an appressorium, a dome-shaped and well melanized infection structure, to penetrate its host. Environmental cues that induce appressorium formation include hydrophobicity and hardness of contact surface and chemicals from its host. Artificial surfaces are widely used to induce appressorium formation, but frequencies of appressorium induction are not always consistent. To understand variable induction of appressorium formation in M. grisea, several factors were tested on GelBond. High levels of appressorium formation were induced over a wide range of temperature (20~3$0^{\circ}C$) and pH (4~7). spore age up to 3-week-old did not significantly affect appressorium formation, but only a few apressoria on GelBond. However, adenosine specifically inhibited appressorium formation. Adenosine inhibition of appressorium formation was restored by exogenous addition of cAMP. Germ tube tips of M. grisea maintained the ability to differentiate appressoria by chemical inducers on GelBond at least up to 16 h after conidia germination. These results suggest that environmental factors have little effect on the variable induction of appressorium formation on the artificial surface in M. grisea.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1999.10a
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• pp.387-394
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• 1999

Artificial Neural Network (ANN) is a computational model inspired by the structure and operations of the brain. It is massively parallel system consisting of a large number of highly interconnected and simple processing units. The purpose of this paper is to verify the applicability of ANN to predict experimental results through the use of measured experimental data. Although there have been accumulated data based on hysteretic characteristics of structural element with cyclic loading tests, it is difficult to directly apply them for the analysis of elastic and plastic response. Thus, simple models with mathematical formula such as Bi-Linear Model, Ramberg-Osgood Model, Degrading Tri Model, Takeda Model, Slip type Model, and etc, have been used. To verify the practicality and capability of this study, ANN is adapted to several models with mathematical formula using numerical data To show the efficiency of ANN in nonlinear analysis, it is important to determine the adequate input and output variables of hysteretic models and to minimize an error in ANN process. The application example is Beam-Column joint test using the ANN in modeling of the linear and nonlinear hysteretic behavior of structure.

• The Korean Journal of Ecology
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• v.21 no.5_3
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• pp.665-673
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• 1998

This study was conducted to clarified the relationship between bird community and forest structure and present the counterplan for protection and management of bird community from February 1993 to July 1995 at deciduous and coniferous forest within Mt. Nam area, Seoul, Korea. DBH distribution has not significant differences in each study site. Deciduous forest had more foliage coverage in all layers than coniferous forest. Total 41 species of birds, which were 16 species of resident, 14 species of summer visitor, 4 species of winter visitor, and 7 species of passage migrant were recrded in two study sites. Leaf use rate of birds was increased the increase of coverage. The number of breeding species and pairs, breeding density, and diversity index were greater in deciduous forest than coniferous forest. The number of species and pairs on bush-nesting and foraging guild were greater than other guilds. And the nuber of species and pairs on hole nesting guild were the fewest in nesting guild. Use rate of artificial nests for improvement of habitat quality was greater in coniferous forest than deciduous forest. Maintenance of bush layer, increase of coverage and leaf layer diversity, supply of artificial nests, management of large trees, and control of natural enemy were necessary for protection and management of bird community in Mt. nam area.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2013.05a
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• pp.98-99
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• 2013

The amount of surface chlorides of architectural structure in incoming salt environment depends on the characteristics of distribution of incoming salt in atmosphere. Therefore, many researches are being conducted on deducting the correlation between incoming salt amount attached to the surface of real structure and that of atmosphere after quantitative measurement. However, in real environment, these studies are somewhat far fetched. That is because incoming salt in atmosphere are changed by various climatic conditions and in the case of the structures surface, attached incoming salt may be carried away due to the rainfall. Therefore, this study aims to draw an improved proportional relation between the amount of sodium chloride in atmosphere and that attached to the surface of architectural structures by measuring the amount attached to each architectural material using artificial incoming salt generator that can control various climatic variables that can be caused in real environment.

• Journal of Surface Science and Engineering
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• v.49 no.2
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• pp.125-129
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• 2016

Anodizing is a technology to generate thicker and high-quality films than natural oxide films by treating metals via electrochemical methods. Electrochemical manufacturing method of nano structure is an efficient technology in terms of cost reduction, high productivity and complicated shapes, which receives the spotlight in diverse areas. Especially, artificial films generated by anodizing technology possess excellent mechanical characteristics including hardness and wear resistance. It is also easy to modify thickness and adjust shape of those artificial films so that they are mainly used in sensors, filters, optical films and electrolytic condensers. In this study, experiment was performed to observe the effect of current density on porous film formation in two-step anodizing for Al alloy. Anodizing process was performed with 10 vol.% sulfuric acid electrolyte while the temperature was maintained at $10^{\circ}C$ using a double beaker. and $10{\sim}30mA/cm^2$ was applied for 40 minutes using a galvanostatic method. As a result, both pore diameters and distances between pores tended to increase as the local temperature and electrolysis activity increased due to the increase in applied current density.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.954-957
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• 2005

In order to implement Artificial Intelligence, various technologies have been widely used. Artificial Intelligence is applied for many industrial product and machine tools are the center of manufacturing devices in intelligent manufacturing system. The purpose of this paper is to present the construction of Rule Base for knowledge structure that is applicable to machine tools. This system is that decision whether to act in accordance with machine status is support system. It constructs Rule Base of knowledge used of machine toots. The constructed Rule Base facilitates the effective operation and control of machine tools and will provide a systematic way to integrate the expert's knowledge that will apply Intelligent Machine Tools.

• Journal of Biomedical Engineering Research
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• v.14 no.2
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• pp.155-162
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• 1993

The human's biomechanical structure keeps an optimal state by adapting the original biomechanical structure according to a change in the physical environment. This phenomenon is believed to be the main cause of loosening of the total hip replacement which is used widely in these days. In this study the bone density change due to artificial hip joint, which is generally believed as bone-remodeling, was investigated by the finite element method. For this, 2-D FEM models with 4 nodal point elements were constructed for intact and implanted cases. The density was calculated by comparing the relative amounts of effective stress for these two cases. In this way, calculated new density values were used in the next step as input values and this procedure repeated until convergence was obtained. Severe density change was detected at the femoral cortex of the proximal-medial side as expected. Moreover, following surprising result was found from this analysis. Titanium alloy prosthesis showed less density change compared to stainless steel prosthesis at earlier stage, however, almost same amount of the density change was detected at final stage. It was also found that other design parameters could not significantly affect its density change.

• International Journal of Naval Architecture and Ocean Engineering
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• v.4 no.2
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• pp.112-122
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• 2012

The damage analysis of coastal structure is very important as it involves many design parameters to be considered for the better and safe design of structure. In the present study experimental data for non-reshaped berm breakwater are collected from Marine Structures Laboratory, Department of Applied Mechanics and Hydraulics, NITK, Surathkal, India. Soft computing techniques like Artificial Neural Network (ANN), Support Vector Machine (SVM) and Adaptive Neuro Fuzzy Inference system (ANFIS) models are constructed using experimental data sets to predict the damage level of non-reshaped berm breakwater. The experimental data are used to train ANN, SVM and ANFIS models and results are determined in terms of statistical measures like mean square error, root mean square error, correla-tion coefficient and scatter index. The result shows that soft computing techniques i.e., ANN, SVM and ANFIS can be efficient tools in predicting damage levels of non reshaped berm breakwater.