• Journal of the Computational Structural Engineering Institute of Korea
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• v.33 no.5
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• pp.303-310
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• 2020

In this study, a method for selection of the location and number of monitoring sensors in a building structure using artificial neural networks is proposed. The acceleration-history values obtained from the installed accelerometers are defined as the input values, and the mass and stiffness values of each story in a building structure are defined as the output values. To select the installation location and number of accelerometers, several installation scenarios are assumed, artificial neural networks are obtained, and the prediction performance is compared. The installation location and number of sensors are selected based on the prediction accuracy obtained in this study. The proposed method is verified by applying it to 6- and 10-story structure examples.

• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2006.09b
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• pp.910-911
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• 2006

We newly designed and manufactured a new arranging system for a three-dimensional artificial crystal of monosized micro particles. In this system, a robotic micro-manipulator accurately locates the spherical particle onto the lattice point, and subsequently fiber lasers micro-weld the contact points between the neighboring particles. Actually, one- and two-dimensional arrays were constructed using monosized tin particles with the diameter of 400 m. Moreover, due to optimization of the process parameters, we successfully constructed the artificial crystals of simple cubic and diamond structures. In particular, the diamond structure which can represent a large photonic band gap is expected to progress toward a practical photonic crystal device.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.98-103
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• 2021

Recently, as the need for food resources has increased both domestically and internationally, support for the agricultural sector for stable food supply and demand is expanding in Korea. However, according to recent media articles, the biggest problem in rural communities is the unstable profit structure. In addition, in order to confirm the profit structure, profit forecast data must be clearly prepared, but there is a lack of auxiliary data for farmers or future returnees to predict farm income. Therefore, in this paper we analyzed data over the past 15 years through time series analysis and proposes an artificial intelligence farm income prediction algorithm that can predict farm household income in the future. If the proposed algorithm is used, it is expected that it can be used as auxiliary data to predict farm profits.

• Earthquakes and Structures
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• v.24 no.2
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• pp.111-126
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• 2023

Highly reliable and versatile methods artificial intelligence (AI) have found multiple application in the different fields of science, engineering and health care system. In the present study, we aim to utilize AI method to investigated vibrations in the human leg bone. In this regard, the bone geometry is simplified as a thick cylindrical shell structure. The deep neural network (DNN) is selected for prediction of natural frequency and critical buckling load of the bone cylindrical model. Training of the network is conducted with results of the numerical solution of the governing equations of the bone structure. A suitable optimization algorithm is selected for minimizing the loss function of the DNN. Generalized differential quadrature method (GDQM), and Hamilton's principle are used for solving and obtaining the governing equations of the system. As well as this, in the results section, with the aid of AI some predictions for improving the behaviors of the various sport systems will be given in detail.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.201-206
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• 1996

This paper presents a new information processing machine which is called artificial brain(ABrain) and considers the structure of artificial neural networks constructed in a RICOH neurocomputer RN-2000 in the ABrain, in order to track given trajectories which are produced in a micro-computer or a moving light by hand in a recognition and tracking system.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.197-204
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• 2013

In this paper, we propose a new method for artificial bandwidth extension of narrow-band signal in frequency domain. In the proposed method, a narrow-band signal is decomposed into excitation signal and spectral envelope, which are extended independently in frequency domain. The excitation signal is extended such that low-band harmonic structure is maintained in high band, and the spectral envelope is extended based on sub-band energy using NMF. Finally, the spectral phase is determined based on signal correlation between frames in time domain, resulting in the final wide-band signal. The subjective evaluation verified that the wide-band signal generated by the proposed method has a higher quality than the original narrow-band signal.

• Journal of the Korean Institute of Landscape Architecture
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• v.26 no.2
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• pp.15-27
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• 1998

The purposes of this study were to investigate vegetation structure and present management planning of mountain type green space using the green space changes during the 20 years, actual vegetation, and plant community structure in land area of Inchon, Korea. The actual vegetation area in survey sites was consisted of Quercus acutissima community, Robinia pseudoacacia forest, Pinus rigida forest, Q. mongolica-Pinus rigida community, P. rigida-Q. mongolica community, Q. monogolica community and so on. According to the classification by TWINSPAN, 61 survey plots were divided into 9 groups; Q. mongolica-Alnus japonica-R. pseudoacacia-P. densiflora, R. pseudoacacia-Styrax japonica, P. rigida-R. pseudoacacia-Q. mongolica, R. pseudoacacia-P. rigida-Q. mongolica-A. hirusta, Q. mongolica-P. thunbergii, and prunus sargentii-Zelkova serrata community. From this result, ecological succession trend of vegetation seems to be change from artificial result, ecological succession trend of vegetation seems to be change from artificial planting forest to native plant community which was dominated by Quercus spp.. This study area need to manage for the increase of biodiversity through the restoration of naturalness by ecological management of artificial planting forest and ecological planting of injured green space.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.03a
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• pp.64-71
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• 2009

The stresses acting on shotcrete lining of tunnel have been measured virtually by monitoring instruments installed during construction. However, the malfunction of instrument and the lack of consistency of signal have always been controversial, but re-installation of instrument after construction of tunnel lining is practically impossible. Therefore, authors have carried out the study to develop a new technique for estimating the stress acting on shotcrete lining during and after construction. In the technique, stresses of shotcrete lining can be estimate by the measurement of deformation of free face. Therefore, the relationships between the stresses of shotcrete lining and deformation of free surface are indispensable factor. In this paper, the parametric study using 2D FEM analysis was carried out to estimate the relationships between the stress level acting on the tunnel shotcrete lining and the deformation near the free face (e.g. artificial crack in this study). The distribution of stresses of shotcrete lining is also investigated in this study as the preliminary investigation for the large-scale tunnel lining test and detailed 3D FEM analysis.

• Smart Structures and Systems
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• v.14 no.2
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• pp.159-189
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• 2014

One of the most important requirements in the evaluation of existing structural systems and ensuring a safe performance during their service life is damage assessment. Damage can be defined as a weakening of the structure that adversely affects its current or future performance which may cause undesirable displacements, stresses or vibrations to the structure. The mass and stiffness of a structure will change due to the damage, which in turn changes the measured dynamic response of the system. Damage detection can increase safety, reduce maintenance costs and increase serviceability of the structures. Artificial Neural Networks (ANNs) are simplified models of the human brain and evolved as one of the most useful mathematical concepts used in almost all branches of science and engineering. ANNs have been applied increasingly due to its powerful computational and excellent pattern recognition ability for detecting damage in structural engineering. This paper presents and reviews the technical literature for past two decades on structural damage detection using ANNs with modal parameters such as natural frequencies and mode shapes as inputs.

• Journal of Information Science Theory and Practice
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• v.10 no.spc
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• pp.12-24
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• 2022

This study attempted to investigate changes in collaboration structure for each stage of national Research and Development (R&D) in the artificial intelligence (AI) field through analysis of a co-author network for papers written under national R&D projects. For this, author information was extracted from national R&D outcomes in AI from 2014 to 2019. For such R&D outcomes, NTIS (National Science & Technology Information Service) information from the KISTI (Korea Institute of Science and Technology Information) was utilized. In research collaboration in AI, power function structure, in which research efforts are led by some influential researchers, is found. In other words, less than 30 percent is linked to the largest cluster, and a segmented network pattern in which small groups are primarily developed is observed. This means a large research group with high connectivity and a small group are connected with each other, and a sporadic link is found. However, the largest cluster grew larger and denser over time, which means that as research became more intensified, new researchers joined a mainstream network, expanding a scope of collaboration. Such research intensification has expanded the scale of a collaborative researcher group and increased the number of large studies. Instead of maintaining conventional collaborative relationships, in addition, the number of new researchers has risen, forming new relationships over time.