• Structural Engineering and Mechanics
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• 제83권3호
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• pp.401-413
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• 2022

The collapse of civil infrastructure due to natural disasters results in financial losses and many casualties. In particular, the recent increase in earthquake activities has highlighted on the importance of assessing the seismic performance and predicting the seismic risk of a structure. However, the nonlinear behavior of a structure and the uncertainty in ground motion complicate the accurate seismic response prediction of a structure. Artificial intelligence can overcome these limitations to reasonably predict the nonlinear behavior of structures. In this study, a deep learning-based algorithm was developed to estimate the time-history seismic response of bridge structures. The proposed deep neural network was trained using structural and ground motion parameters. The performance of the seismic response prediction algorithm showed the similar phase and magnitude to those of the time-history analysis in a single-degree-of-freedom system that exhibits nonlinear behavior as a main structural element. Then, the proposed algorithm was expanded to predict the seismic response and fragility prediction of a bridge system. The proposed deep neural network reasonably predicted the nonlinear seismic behavior of piers and bearings for approximately 93% and 87% of the test dataset, respectively. The results of the study also demonstrated that the proposed algorithm can be utilized to assess the seismic fragility of bridge components and system.

• International Journal of Computer Science & Network Security
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• 제22권8호
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• pp.357-361
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• 2022

The paper demonstrates how the Islamic governments in the Islamic history derived the authority for regulations and laws from the Qur'ān and the Sunna (sayings of the Prophet). These two laws are sovereign over public policy. Then, it shows the obstacles that prevented modern Muslim countries from formulating public policy based on Sharia law.

• Structural Engineering and Mechanics
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• 제44권3호
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• pp.379-403
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• 2012

In recent years, the need for optimal design of structures under time-history loading aroused great attention in researchers. The main problem in this field is the extremely high computational demand of time-history analyses, which may convert the solution algorithm to an illogical one. In this paper, a new framework is developed to solve the size optimization problem of steel truss structures subjected to ground motions. In order to solve this problem, the covariance matrix adaptation evolution strategy algorithm is employed for the optimization procedure, while a generalized regression neural network is utilized as a meta-model for fitness approximation. Moreover, the computational cost of time-history analysis is decreased through a wavelet analysis. Capability and efficiency of the proposed framework is investigated via two design examples, comprising of a tower truss and a footbridge truss.

• International Journal of Contents
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• 제11권1호
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• pp.52-61
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• 2015

In the past decade, East Asian Research has received attention from researchers as well as in South Korea society-at-large. The broad category of East Asian Research includes various disciplinary fields, such as "history, economics, and politics; however, few studies have used quantitative analysis to explore its development. In this paper, we used network analysis to identify the disciplines and active research areas, focusing on productivity, collaboration patterns, and citation networks of East Asian Research in South Korea. For this study, 6,646 journal publications related with East Asian Research and indexed by KCI (Korean Citation Index) during the 10-year period of 2004-2013 were considered. Results show that East Asian Research was led during this period by sole-researchers, rather than interdisciplinary studies. Moreover, a co-institution network represents active institutions with a high degree and collaborative centrality. In terms of journal-journal citation networks, journals belonging to both "history" and "Korean literature" disciplines were dominant.

• 한국기록관리학회지
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• 제19권1호
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• pp.275-281
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• 2019

본 글은 2018년 김포문화재단에서 주관한 김포시 북변동 스토리텔링 사업을 소개한 글이다. 프로젝트는 지역의 역사와 문화자원을 아카이빙 하기 위해서 수행되었다. 세부 과업으로는 조사, 답사, 구술채록, 스토리 정리, 콘텐츠 활용방안 제시 등이었다. 이와 함께 프로젝트를 수행하는 과정에서 느낀 프로젝트의 한계와 의미, 지역 역사문화자원 발굴의 의미, 지역 아카이브의 필요성을 함께 보고한다.

• 한국지하수토양환경학회지:지하수토양환경
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• 제20권3호
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• pp.51-64
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• 2015

In the present study, we develop two history matching techniques based on Markov chain Monte Carlo method where radial basis function and Gaussian distribution generated by unconditional geostatistical simulation are employed as the random walk transition kernels. The Bayesian inverse methods for aquifer characterization as the developed models can be effectively applied to the condition even when the targeted information such as hydraulic conductivity is absent and there are transient hydraulic head records due to imposed stress at observation wells. The model which uses unconditional simulation as random walk transition kernel has advantage in that spatial statistics can be directly associated with the predictions. The model using radial basis function network shares the same advantages as the model with unconditional simulation, yet the radial basis function network based the model does not require external geostatistical techniques. Also, by employing radial basis function as transition kernel, multi-scale nested structures can be rigorously addressed. In the validations of the developed models, the overall predictabilities of both models are sound by showing high correlation coefficient between the reference and the predicted. In terms of the model performance, the model with radial basis function network has higher error reduction rate and computational efficiency than with unconditional geostatistical simulation.

• 한국의사학회지
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• 제28권1호
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• pp.1-10
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• 2015

This study examines the meaning of medical-text publication in the Joseon Dynasty by applying anthropological notions of "health care system" and "popular health care sector" to the social and political contexts of the pre-modern state. The present study focuses on the social network of senders and receivers in which medical knowledge is communicated and shared. Exploring the multi-layered structure of the network among the state, the author-practitioners, and populace, this study argues that the network of knowledge sharing system by publication of medical texts itself is a core structure in the health care system of the Joseon Dynasty. This pre-modern health care system aimed to vitalize and reinforce the "popular health care sector" by sharing medical knowledge with populace through the book-publication system. Foucault's notion of "biopolitics" provides a comparative window between the modern health care system and the health care system of the Joseon period, articulating the particularity of the pre-modern health care system.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2009년도 추계학술대회
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• pp.1018-1021
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• 2009

무선 센서 네트워크는 특정지역에서 데이터를 수집하여 처리는 작은 센서 노드들로 구성된다. 이러한 센서들은 최초로 설치된 이후에는 배터리로 동작되며, 동작기간이 수개월에서 수년까지 지속되어야 함으로 제한된 자원을 효율적으로 활용할 수 있어야 한다. 본 논문에서는 데이터 중심개념을 적용한 Directed Diffusion의 기본동작구조에 RHC(rounting history cache)를 적용하여, 데이터 전송경로 설정에 신뢰성과 효율성을 높인다. 제안하는 RHC 알고리즘은 각 센서노드가 자신의 RHC를 주기적으로 업데이트하여 최적화경로를 저장하고 있기 때문에, 이벤트 발생시마다 경로를 재설정하여 에너지가 낭비되는 것을 최소화 하였고, 중복메시지의 최소화로 신뢰성을 향상시켰다.

• 전기학회논문지
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• 제65권10호
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• pp.1731-1737
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• 2016

In this paper, a method is proposed to recognize human actions as nonverbal expression; the proposed method is composed of two steps which are action representation and action recognition. First, MHI(Motion History Image) is used in the action representation step. This method includes segmentation based on depth information and generates spatio-temporal templates to describe actions. Second, CNN(Convolution Neural Network) which includes feature extraction and classification is employed in the action recognition step. It extracts convolution feature vectors and then uses a classifier to recognize actions. The recognition performance of the proposed method is demonstrated by comparing other action recognition methods in experimental results.

• 컴퓨터교육학회논문지
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• 제3권1호
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• pp.177-189
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• 2000

본 연구에서는 의미망 이론을 웹 코스웨어에 적용하기 위한 효과적인 코스웨어 설계 모델을 구안하고 웹에서 운영할 수 있는 국사과 웹 코스웨어를 구현하였다. 웹 코스웨어의 설계 모델은 구성주의 학습모델 중에서 인지적 융통성 모델을 응용하였고 의미망을 활용한 하이퍼텍스트기법을 적용하여 내용 주제간 관계의 유형을 정의하였다. 이를 바탕으로 내용 지식의 지도를 개발하였으며 국사과 지식 데이터베이스를 구축하는 방안을 제시하고 구현하였다.