• Earthquakes and Structures
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• v.10 no.1
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• pp.25-51
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• 2016

In this study, graph product rules are applied to the dynamic analysis of regular skeletal structures. Graph product rules have recently been utilized in structural mechanics as a powerful tool for eigensolution of symmetric and regular skeletal structures. A structure is called regular if its model is a graph product. In the first part of this paper, the formulation of time history dynamic analysis of regular structures under seismic excitation is derived using graph product rules. This formulation can generally be utilized for efficient linear elastic dynamic analysis using vibration modes. The second part comprises of random vibration analysis of regular skeletal structures via canonical forms and closed-form eigensolution of matrices containing special patterns for symmetric structures. In this part, the formulations are developed for dynamic analysis of structures subjected to random seismic excitation in frequency domain. In all the proposed methods, eigensolution of the problems is achieved with less computational effort due to incorporating graph product rules and canonical forms for symmetric and cyclically symmetric structures.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06e
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• pp.129-132
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• 1998

A bond graph modeling approach which is equivalent to a finite element method is formulated in the case of the piezoelectric thickness vibrator. This formulation suggests a new definition of the generalized displacements for a continuous system as well as the piezoelectric thickness vibrator. The newly defined coordinates are illustrated to be easily interpreted physically and easily used in analysis of the system performance. The bond graph model offers the primary advantage of physical realizability and has a greater physical accuracy because of the use of multiport energic elements. While results are presented is general in scope and can be applied to arbitrary physical systems.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.522-524
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• 2012

For exact classification of the defect, good feature selection and classifier is necessary. In this paper, various features such as brightness features, shape features and statistical features are stated and Bayes classifier using Gaussian mixture model is used as classifier. Also feature extraction method based on spectral graph theory is presented. Experimental result shows that feature extraction method using graph Laplacian result in better performance than the result using PCA.

• Journal of the Korean Institute of Navigation
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• v.22 no.2
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• pp.81-87
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• 1998

On this paper, the methods of optimization research of the fishing navigation using the graph theory are substantiated on the basis of the proposed probable model of the fishing vessel navigator's activity. The graph theory is concered about the transitionform the top graph to the rib one. And the definition of the additional system elements (quasi elements) necessary to provide the effectiveness during the fishing navigation are also substantiated herein. This approach helps to optimize the structure of any fishing vessel monitoring system.

• ETRI Journal
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• v.39 no.4
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• pp.592-604
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• 2017

Intrusion detection is very important for network situation awareness. While a few methods have been proposed to detect network intrusion, they cannot directly and effectively utilize semi-quantitative information consisting of expert knowledge and quantitative data. Hence, this paper proposes a new detection model based on a directed acyclic graph (DAG) and a belief rule base (BRB). In the proposed model, called DAG-BRB, the DAG is employed to construct a multi-layered BRB model that can avoid explosion of combinations of rule number because of a large number of types of intrusion. To obtain the optimal parameters of the DAG-BRB model, an improved constraint covariance matrix adaption evolution strategy (CMA-ES) is developed that can effectively solve the constraint problem in the BRB. A case study was used to test the efficiency of the proposed DAG-BRB. The results showed that compared with other detection models, the DAG-BRB model has a higher detection rate and can be used in real networks.

• Journal of Computing Science and Engineering
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• v.10 no.3
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• pp.85-94
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• 2016

We propose a model-based method for information alignment using educational standards as a case study. Discrepancies and inconsistencies in educational standards across different states/cities hinder the retrieval and sharing of educational resources. Unlike existing educational standards alignment systems that only give binary judgments (either "aligned" or "not-aligned"), our proposed system classifies each pair of educational standard statements in one of seven levels of alignments: Strongly Fully-aligned, Weakly Fully-aligned, Partially-$aligned^{***}$, Partially-$aligned^{**}$, Partially-$aligned^*$, Poorly-aligned, and Not-aligned. Such a 7-level categorization extends the notion of binary alignment and provides a finer-grained system for comparing educational standards that can broaden categories of resource discovery and retrieval. This study continues our previous use of mathematics education as a domain, because of its generally unambiguous concepts. We adopt a materialization pattern (MP) model developed in our earlier work to represent each standard statement as a verb-phrase graph and a noun-phrase graph; we align a pair of statements using graph matching based on Bloom's Taxonomy, WordNet, and taxonomy of mathematics concepts. Our experiments on data sets of mathematics educational standards show that our proposed system can provide alignment results with a high degree of agreement with domain expert's judgments.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.799-805
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• 1996

In many cases, the magnetic farce model is linearized at the origin in designing the controller of a magnetic bearing system. However. this linear assumption is violated by the unmodeled nonlinear effect such as sensor dislocation and backup bearing dislocation. Therefore, a direct probe into the nonlinear magnetic force model in an active magnetic bearing system is necessary. To analyze the nonlinear magnetic force model of a magnetic bearing system, phase plot analysis which is to plot the numerical solution of the nonlinear equation in several initial points in the interested region is applied. Phase plot analysis is used to observe a nonlinear dynamic system qualitatively (not quantitatively). With this method, we can get much useful information of the nonlinear system. Among this information, a bifurcation graph that represents stability and locations of fixed points is essential. From the bifurcation graph, a stability criterion of magnetic bearing system is derived.

• Safety and Health at Work
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• v.12 no.1
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• pp.42-50
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• 2021

Introduction: Despite huge investments in new technology and transportation infrastructure, terrible accidents still remain a reality of traffic. Methods: Severe traffic accidents were analyzed from four prevailing modes of today's transportations: sea, air, railway, and road. Main root causes of all four accidents were defined with implementation of the approach, based on Flanagan's critical incident technique. In accordance with Molan's Availability Humanization model (AH model), possible preventive or humanization interventions were defined with the focus on technology, environment, organization, and human factors. Results: According to our analyses, there are significant similarities between accidents. Root causes of accidents, human behavioral patterns, and possible humanization measures were presented with rooted graphs. It is possible to create a generalized model graph, which is similar to rooted graphs, for identification of possible humanization measures, intended to prevent similar accidents in the future. Majority of proposed humanization interventions are focused on organization. Organizational interventions are effective in assurance of adequate and safe behavior. Conclusions: Formalization of root cause analysis with rooted graphs in a model offers possibility for implementation of presented methods in analysis of particular events. Implementation of proposed humanization measures in a particular analyzed situation is the basis for creation of safety culture.

• The Korean Journal of Applied Statistics
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• v.37 no.3
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• pp.355-380
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• 2024

In this paper, we compare the performance of graph-based deep learning models using OECD test guideline (TG) data. OECD TG are a unique tool for assessing the potential effects of chemicals on health and environment. but many guidelines include animal testing. Animal testing is time-consuming and expensive, and has ethical issues, so methods to find or minimize alternatives are being studied. Deep learning is used in various fields using chemicals including toxicity prediciton, and research on graph-based models is particularly active. Our goal is to compare the performance of graph-based deep learning models on OECD TG data to find the best performance model on there. We collected the results of OECD TG from the website eChemportal.org operated by the OECD, and chemicals that were impossible or inappropriate to learn were removed through pre-processing. The toxicity prediction performance of five graph-based models was compared using the collected OECD TG data and MoleculeNet data, a benchmark dataset for predicting chemical properties.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2D
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• pp.171-179
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• 2010

The purpose of the present study is to suggest composing the graph topology of sketch drawing element and the recognition of the shape pattern for the earthwork quantity calculation. The algorithm which can extract the topology element such as vertex, edge, face and establish the relation between each topology was developed. The model which can define earthwork graph and recognize the shape pattern of earthwork was presented. As a result of the study, the shape pattern of earthwork that can't be calculated by existing earthwork calculation program could be recognized as expanding this model. The earthwork shape recognition automation using the graph topology model can be applied to the automation for the earthwork quantity estimation.