• Geomechanics and Engineering
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• 제27권6호
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• pp.605-614
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• 2021

Water inrush from fault is one of the most severe hazards during tunnel excavation. However, the traditional evaluation methods are deficient in both quantitative evaluation and uncertainty handling. In this paper, a comprehensive methodology method combined intuitionistic fuzzy AHP with a Bayesian network for the risk assessment of water inrush from fault in the subsea tunnel was proposed. Through the intuitionistic fuzzy analytic hierarchy process to replace the traditional expert scoring method to determine the prior probability of the node in the Bayesian network. After the field data is normalized, it is classified according to the data range. Then, using obtained results into the Bayesian network, conduct a risk assessment with field data which have processed of water inrush disaster on the tunnel. Simultaneously, a sensitivity analysis technique was utilized to investigate each factor's contribution rate to determine the most critical factor affecting tunnel water inrush risk. Taking Qingdao Kiaochow Bay Tunnel as an example, by predictive analysis of fifteen fault zones, thirteen of them are consistent with the actual situation which shows that the IFAHP-Bayesian Network method is feasible and applicable. Through sensitivity analysis, it is shown that the Fissure development and Apparent resistivity are more critical comparing than other factor especially the Permeability coefficient and Fault dip. The method can provide planners and engineers with adequate decision-making support, which is vital to prevent and control tunnel water inrush.

• 전자공학회논문지A
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• 제32A권8호
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• pp.1-10
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• 1995

We have analyzed the reliability of failure models in circuit-switched networks. These models are grid topology circuit-switched networks, and each node transmits a packet to a destination node using a Flooding routing method. We have assumed that the failure of each link and node is independent. We have considered two method to analyze reliability in these models : The Karnaugh Map method and joint probability method. In this two method, we have analyzed the reliability in a small grid topology circuit switched network by a joint probability method, and comared analytic results with simulated ones. For a large grid enormous. So, we have evaluated the reliability of the network by computer simulation techniques. As results, we have found that the analytic results are very close to simulated ones in a small grid topology circuit switched network. And, we have found that network reliability decreases exponentially, according to increment of link or node failure, and network reliability is almost linearly decreased according to increment of the number of links, by which call has passed. Finally, we have found an interesting result that nodes in a center of the network are superior to the other nodes from the reliability point of view.

• 한국강구조학회 논문집
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• 제10권3호통권36호
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• pp.463-472
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• 1998

본 논문의 목적은 4각형네트워크 패턴을 가지는 단층래티스돔의 좌굴특성을 실험과 이론을 통하여 검토하고, 나아가 4각형 네트워크 단층돔에 대한 신뢰할 수 있는 이론해석법을 개발하기 위한 기초연구를 하는데 그 목적이 있다. 이론해석은 야마다의 연속체치환법과 유한요소법에 의한 프레임해석법으로 한다. 원주방향에 대한 불균일한 강성과 지붕재료의 강성이 돔전체 좌굴특성에 미치는 영향을 검토한다. 이론과 실험에 의한 결과는 불균일한 강성을 가지거나 또는 강성을 갖는 지붕재료를 사용하는 다양한 종류의 단층래티스돔에 대한 일반적인 이론해석법을 개발하기 위한 기초자료로 활용될 것이다.

• 한국문헌정보학회지
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• 제49권3호
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• pp.457-488
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• 2015

본 연구는 1990년부터 2014년까지 25년 간 국외 유수 문헌정보학 학술지들에 게재된 논문들을 대상으로 연구 주제와 연구 방법을 구분하여 현 선도 학술지의 연구 누적 현황을 분석하였다. 연구 주제와 연구 방법을 구분하고 그들 간의 관계를 살펴보기 위해 가중 주제-방법 네트워크를 개발하였다. 이는 주제와 방법으로 구성된 네트워크이며, 해당 토픽 소속 단어의 동시 출현 빈도를 기초로 주제와 방법에 가중치를 준다. 본 연구 결과에 따르면, 지난 25년간 경영정보시스템, 정보요구분석, 계량서지연구, 정보정책 등이 상위 연구 주제들이었다. 또한, 모델링, 개념/문헌연구, 연구협업분석, 웹데이터 분석 등이 상위 연구 방법들이었으며, 최근 텍스트 마이닝의 비상이 괄목할 만하다. 빈번히 짝을 이루는 연구 주제들과 연구 방법들의 지난 25년간의 군집들과 최근 5년간의 군집들을 살펴보면, 계량서지연구가 네트워크분석 방법들을 다수 적용하면서 그 저변을 넓히며 자리를 확고하게 하고 있으며, 텍스트 마이닝이 의료정보시스템, 이용자인터페이스에 특화되고 있음을 확인할 수 있다. 이러한 연구 결과는 문헌정보학의 선도 연구자들의 관심 연구 영역과 관점을 확인시켜주고, 향후 문헌정보학 발전을 위한 연구 설계의 기초자료로 활용될 수 있다.

• 디지털산업정보학회논문지
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• 제11권4호
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• pp.47-60
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• 2015

In this paper, we propose a simple and useful method using a port role to visualize the network attacks. The port role defines the behavior of the port from the source and destination port number of network session. Based on the port role, the port provides the brief security features of each node as an attacker, a victim, a server, and a normal host. We have automatically classified and identified the type of node based on the port role and security features. We detected and visualized the network attacks using these features of the node by the port role. In addition, we are intended to solve the problems with existing visualization technologies which are the reflection problem caused an undirected network session and the problem caused decreasing of distinct appearance when occurs a large amount of the sessions. The proposed method monitors anomalies occurring in an entire network and displays detailed information of the attacker, victim, server, and hosts. In addition, by providing a categorized analysis of network attacks, this method can more precisely detect and distinguish them from normal sessions.

• 한국멀티미디어학회논문지
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• 제22권4호
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• pp.455-462
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• 2019

This paper proposes a method of utilizing convolutional neural network to classify the images of Bender Gestalt Test (BGT), which is a tool to understand and analyze a person's characteristic. The proposed network is composed of 29 layers including 18 convolutional layers and 2 fully connected layers, where the network is to be trained with augmented images. To verify the proposed method, 10 fold validation was adopted. In results, the proposed method classified the images into 9 classes with the mean f1 score of 97.05%, which is 13.71%p higher than a previous method. The analysis of the results shows the classification accuracy of the proposed method is stable over all the patterns as the worst f1 score among all the patterns was 92.11%.

• Steel and Composite Structures
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• 제51권6호
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• pp.713-727
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• 2024

Damage detection in structures using the change of modal parameters (modal shapes and natural frequencies) has achieved satisfactory results. However, as modal shapes and natural frequencies alone may not provide enough information to accurately detect damages. Therefore, a hybrid singular value decomposition and deep belief network approach is developed to effectively identify damages in aluminum plate structures. Firstly, damage locations are determined using singular value decomposition (SVD) to reveal the singularities of measured displacement modal shapes. Secondly, using experimental modal analysis (EMA) to measure the natural frequencies of damaged aluminum plates as inputs, deep belief network (DBN) is employed to search damage severities from the damage evaluation database, which are calculated using finite element method (FEM). Both simulations and experimental investigations are performed to evaluate the performance of the presented hybrid method. Several damage cases in a simply supported aluminum plate show that the presented method is effective to identify multiple damages in aluminum plates with reasonable precision.

• 한국컴퓨터정보학회논문지
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• 제24권7호
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• pp.135-141
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• 2019

The purpose of this study is to extract the key words from the list of research subjects related to 'hotel workers' published in recent 10 years(2009~2018) by using the language network analysis method and to confirm the relation between the key words. In this paper, we propose a semantic network analysis that can overcome limitations of longitudinal study, analyze the recent research trends, and widely use as a research model. The results of this study are as follows ; First, in analyzing major key words in the title of 'Hotel Employer' in recent 10 years, the major keyword of job satisfaction(40), special grade(26), organizational commitment(20), emotional labor(19), service(12), restaurant(10), and turnover intention(9). Second, we analyzed the relation of language network among major key words extracted from the study title of 'hotel workers'. Such a research process is expected to grasp the trends of research related to 'hotel workers' and give implications for the future direction of related research.

• Structural Engineering and Mechanics
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• 제18권3호
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• pp.303-314
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• 2004

An artificial neural network (ANN) application is presented for flexural and axial vibration analysis of elastic beams with various support conditions. The first three natural frequencies of beams are obtained using multi layer neural network based back-propagation error learning algorithm. The natural frequencies of beams are calculated for six different boundary conditions via direct solution of governing differential equations of beams and Rayleigh's approximate method. The training of the network has been made using these data only flexural vibration case. The trained neural network, however, had been tested for cantilever beam (C-F), and both end free (F-F) in case the axial vibration, and clamped-clamped (C-C), and Guided-Pinned (G-P) support condition in case the flexural vibrations which were not included in the training set. The results found by using artificial neural network are sufficiently close to the theoretical results. It has been demonstrated that the artificial neural network approach applied in this study is highly successful for the purposes of free vibration analysis of elastic beams.

• 품질경영학회지
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• 제47권2호
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• pp.315-325
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• 2019

Purpose: The purpose of this study was to propose useful standards evaluation method using standards networks by analyzing the relationship between normative references citation information list. Methods: The collected data through the survey were analyzed using social network analysis. The measurement tools used for this study were divided into three dimensions such as certificate standard, normative reference and degree centrality. Results: The results of this study are as follows; regarding the influence of standard information, It is meaningful that the research using normative reference item among the bibliography information that the standard itself possesses. The analysis of social network analysis data of population standard, normative reference and the correlation analysis with sales, a variable representing actual utilization performance, suggested the importance of the standard and how to evaluate it. Conclusion: In prioritizing standard maintenance, more efficient management will be possible if centrality figures of standard network information are analyzed and used for standard maintenance.