• Structural Engineering and Mechanics
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• v.83 no.3
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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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• v.22 no.8
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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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• v.44 no.3
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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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• v.11 no.1
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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.

• Journal of Korean Society of Archives and Records Management
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• v.19 no.1
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• pp.275-281
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• 2019

This article introduces the storytelling project about Bukbyeon-dong, Gimpo-si by the Kimpo Cultural Foundation in 2018. The project archives local history and culture and includes research, exploration, oral history, story organization, and presentation of ways to utilize contents. Through this, the article aims to present the limitations and importance of the project, the meaning of the excavation of local historical and cultural resources, and the need for local archives.

• Journal of Soil and Groundwater Environment
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• v.20 no.3
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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.

• The Journal of Korean Medical History
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• v.28 no.1
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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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.1018-1021
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• 2009

Wireless Sensor Network collects a data from the specific area and the control is composed of small sensor nodes. Like this sensors to after that is established at the beginning are operated with the battery, the operational duration until several years must be continued from several months and will be able to apply the resources which is restricted in efficiently there must be. In this paper RHC (rounting history cache) applies in Directed Diffusion which apply a data central concept a reliability and an efficiency in data transfer course set. RHC algorithms which proposes each sensor node updated RHC of oneself with periodic and because storing the optimization course the course and, every event occurrence hour they reset the energy is wasted the fact that a reliability with minimization of duplication message improved.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.10
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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.

• The Journal of Korean Association of Computer Education
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• v.3 no.1
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• pp.177-189
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• 2000

This paper describes the design and implementation of Korean History Web courseware using semantic network in order to build learning environment in the viewpoint of cognitive flexibility theory. The most important thing in design for a courseware using semantic network is to build learning environment. The first step to do this is to analyze learning contents and after that we should define the type of link between learning subjects. We should develope the knowledge map which has the link of each type connected with every learning subject.