• 한국전산구조공학회논문집
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• 제33권5호
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• pp.303-310
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• 2020

본 연구에서는 인공신경망을 이용해 건물 구조물의 가속도계 설치 위치 및 개수를 선정하는 방법을 제안한다. 인공신경망의 입력층에는 층에 설치되는 가속도계로부터 얻는 가속도이력데이터가 입력되며, 출력층에는 구조물을 정의하는 각 층의 질량과 강성 값을 출력하도록 신경망을 구성한다. 가속도계의 설치 위치 및 개수를 선정하기 위해 여러 설치 시나리오를 가정하고 훈련을 통해 인공신경망을 구한다. 훈련에 사용되지 않은 예제를 이용해 예측 성능을 비교하였다. 센서 개수 및 위치에 따른 예측 성능을 비교하여 설치위치 및 개수를 선정한다. 6층과 10층 예제 적용을 통해 제안하는 방법을 검증하였다.

• 한국분말야금학회:학술대회논문집
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• 한국분말야금학회 2006년도 Extended Abstracts of 2006 POWDER METALLURGY World Congress Part2
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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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• 제10권4호
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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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• 제24권2호
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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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• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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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.

• 전자공학회논문지
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• 제50권12호
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• pp.197-204
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• 2013

본 논문에서는 주파수 영역에서 협대역 신호를 광대역으로 확장하는 새로운 인공 대역 확장 기술을 제안한다. 제안한 기술은 협대역 신호를 여기 신호와 스펙트럼 포락선 성분으로 분리하고, 주파수 영역에서 각각 독립적인 방법으로 확장한다. 여기 신호는 저대역의 하모닉 구조가 고대역에서 유지되도록 확장하고, 스펙트럼 포락선은 부대역별 에너지를 기반으로 NMF방법으로 확장한다. 마지막으로 시간 축에서 프레임 사이의 상관관계를 기반으로 스펙트럼 위상을 결정하여 최종 광대역 신호를 생성한다. 주관적 청취 평가를 통하여 제안한 방법으로 대역 확장된 신호가 원 협대역 신호보다 음질이 향상된 것을 확인하였다.

• 한국조경학회지
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• 제26권2호
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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.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2009년도 춘계 학술발표회
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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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• 제14권2호
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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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• 제10권spc호
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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.