• Journal of the Korean Institute of Gas
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• v.16 no.6
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• pp.41-47
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• 2012

There are PFD(Process Flow Diagram) and P&ID(Piping and Instrument Diagram) for designing and managing chemical process efficiently. They provide the operation condition and equipment specifications of chemical process, but they do not provide the reliability of chemical process. Therefore, in this study, Reliability Flow Diagram(RFD) which provide the cycle and time of preventive maintenance has been developed using Directed Graph Analysis methodology. Directed Graph Analysis methodology is capable of assessing the reliability of chemical process. It models chemical process into Directed Graph with nodes and arcs and assesses the reliability of normal operation of chemical process by assessing Directed Graph sequential. In this paper, the chemical process reliability transition according to operation time was assessed. And then, Reliability Flow Diagram has been developed by inserting the result into P&ID. Like PFD and P&ID, Reliability Flow Diagram provide valuable and useful information for the design and management of chemical process.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.4008-4023
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• 2022

Since machine learning was introduced into cross-site scripting (XSS) attack detection, many researchers have conducted related studies and achieved significant results, such as saving time and labor costs by not maintaining a rule database, which is required by traditional XSS attack detection methods. However, this topic came across some problems, such as poor generalization ability, significant false negative rate (FNR) and false positive rate (FPR). Moreover, the automatic clustering property of graph convolutional networks (GCN) has attracted the attention of researchers. In the field of natural language process (NLP), the results of graph embedding based on GCN are automatically clustered in space without any training, which means that text data can be classified just by the embedding process based on GCN. Previously, other methods required training with the help of labeled data after embedding to complete data classification. With the help of the GCN auto-clustering feature and labeled data, this research proposes an approach to detect XSS attacks (called GCNXSS) to mine the dependencies between the units that constitute an XSS payload. First, GCNXSS transforms a URL into a word homogeneous graph based on word co-occurrence relationships. Then, GCNXSS inputs the graph into the GCN model for graph embedding and gets the classification results. Experimental results show that GCNXSS achieved successful results with accuracy, precision, recall, F1-score, FNR, FPR, and predicted time scores of 99.97%, 99.75%, 99.97%, 99.86%, 0.03%, 0.03%, and 0.0461ms. Compared with existing methods, GCNXSS has a lower FNR and FPR with stronger generalization ability.

• Journal of Internet Computing and Services
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• v.6 no.6
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• pp.117-125
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• 2005

The dominator tree presents the dominance frontier from directed graph to the tree. we present the effective algorithm for constructing the dominator tree from arbitrary directed graph. The reducible flow graph was reduced to dominator tree after dominator calculation. And the irreducible flow graph was constructed to dominator-join graph using join-edge information of information table. For reducing the dominator tree from dominator-join graph, we implement the effective sequency reducible algorithm and delay reducible algorithm. As a result of implementation, we can see that the delay reducible algorithm takes less execution time than the sequency reducible algorithm. Therefore, we can reduce the flow graph to dominator tree effectively.

• International Union of Geodesy and Geophysics Korean Journal of Geophysical Research
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• v.25 no.1
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• pp.23-34
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• 1997

Seismic tomography using the graph theoretical method of ray tracing is performed in two synthetic data sets with laterally varying velocity structures. The straight-ray tomography shows so poor results in imaging the laterally varying velocity structure that the ray-traced tomographic techniques should be used. Conventional ray tracing methods have serious drawbacks, i.e. problems of convergence and local minima, when they are applied to seismic tomography. The graph theretical method finds good approximated raypaths in rapidly varying media even in shadow zones, where shooting methods meet with convergence problems. The graph theoretical method ensures the globally minimal traveltime raypath while bending methods often cause local minima problems. Especially, the graph theoretical method is efficient in case that many sources and receivers exist, since it can find the traveltimes and corresponding raypaths to all receivers from a specific source at one time. Moreover, the algorithm of graph theoretical method is easily applicable to the ray tracing in anisotropic media, and even to the three dimensional case. Among the row-active inversion techniques, the conjugate gradient (CG) method is used because of fast convergence and high efficiency. The iterative sequence of the ray tracing by the graph theoretical method and the inversion by the CG method is an efficient and robust algorithm for seismic tomography in laterally varying velocity structures.

• Journal of Korean Elementary Science Education
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• v.31 no.3
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• pp.386-397
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• 2012

The purpose of this study was to find a way to improve the science textbook graph through analyzing teachers' interpretation process with eye movement tracking when they try to read the science textbook graph. Participants in this project were 10 elementary school teachers while bar graphs, line graphs, pie charts in 2007 revision science textbooks were used as materials. SMI (SensoMotoric Instruments)' iView X TM RED 120 Hz was used in order to collect eye movement data. Although subjects paid attention to the title of the graph at first, the consequence of the eye fixation was changed by the composition of the graph in case of the rest of areas. In particular, the flow of visual attention and fixation time were affected by the form and configuration of the graph. The diversity of graph construction caused confusion in interpreting graphs; the manner of presenting title, the difference of background colors, size of characters, the name of X-axis and Y-axis. Out results showed that the conformation of graphs as well as the presentation of each factor should be composed in accordance with the educational purpose for helping users to easier understanding.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.251-258
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• 2009

Data mining is a method that extract useful knowledges from huge size of data. Recently, a focussing research part of data mining is to find interesting patterns in graph databases. More efficient methods have been proposed in graph mining. However, graph analysis methods are in NP-hard problem. Graph pattern mining based on pattern growth method is to find complete set of patterns satisfying certain property through extending graph pattern edge by edge with avoiding generation of duplicated patterns. This paper suggests an efficient approach of reducing computing time of pattern growth method through pattern growth's property that similar patterns cause similar tasks. we suggest pruning methods which reduce search space. Based on extensive performance study, we discuss the results and the future works.

• ETRI Journal
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• v.39 no.2
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• pp.255-263
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• 2017

This paper proposes a graph-theatrical approach to optimize spatial reuse by adopting a technique that quantizes the channel information into single bit sub-messages. First, we introduce an interference graph to model the network topology. Based on the interference graph, the computational requirements of the algorithm that computes the optimal spatial reuse factor of each user are reduced to quasilinear time complexity, ideal for practical implementation. We perform a resource allocation procedure that can maximize the efficiency of spatial reuse. The proposed spatial reuse scheme provides advantages in beamforming systems, where in the interference with neighbor nodes can be mitigated by using directional beams. Based on results of system level measurements performed to illustrate the physical interference from practical millimeter wave wireless links, we conclude that the potential of the proposed algorithm is both feasible and promising.

• Transactions of the Korean Society of Automotive Engineers
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• v.6 no.4
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• pp.66-75
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• 1998

In many case of optimal design and sensitivity analysis, obtaining of transfer function between input and output variables is a difficult and time-consuming problem. The bond graph modeling is a method that is used for making it easy to analyze complex systems composed of mechanical and electrical parts. It gives us a simple and systematic tool to get state-space equations easily. And we can obtain the transfer function graphically using bond graph and Mason's rule. This paper shows how bond graphs are converted to block diagram and how Mason's rule is applied. And the simple direct method to obtain transfer function from bond graph is introduced. As a example, induction of transfer function of electric power steering composed of mechanical and electrical parts will be done.

• Journal of the Korea Society of Computer and Information
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• v.21 no.1
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• pp.25-31
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• 2016

There are many methods to describe the importance of a node, centrality, in a graph. In this paper, we focus on the eigenvector centrality. In this paper, an analytical method to estimate the difference of centrality with an additional edge in a graph is proposed. In order to validate the analytical method to estimate the centrality, two problems, to decide an additional edge that maximizes the difference of all centralities of all nodes in the graph and to decide an additional edge that maximizes the centrality of a specific node, are solved using three kinds of random graphs and the results of the estimated edge and observed edge are compared. Though the estimated centrality difference is slightly different from the observed real centrality in some cases, it is shown that the proposed method is effective to estimate the centrality difference with a short running time.