• Journal of the Korean Society of Safety
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• v.18 no.2
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• pp.64-72
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• 2003

A new reliability assessment methodology is presented and the new method is compared with fault tree analysis. The system is modeled by directed graph at a new methodology, which is composed of nodes and arcs. The directed graph corresponds to the layout of chemical process and is easy to construct. Therefore, the directed graph analysis is applicable to the chemical process that has complex sequence. The example of fault tree analysis and directed graph analysis is given. The directed graph analysis has proved to be a valuable and useful method for the reliability assessment of chemical process.

• 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.

• Journal of applied mathematics & informatics
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• v.42 no.1
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• pp.159-167
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• 2024

The Topological indices are known as Mathematical characterization of molecules. In this paper, we have studied line graph of subdivision and semi-total point graph of triangular benzenoid, polynomino chains of 8-cycles and graphene sheet through forgotten and first Zagreb indices.

• Journal of the Korean Society of Combustion
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• v.16 no.2
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• pp.16-22
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• 2011

It is a challenging task to apply large detailed chemical mechanisms of fuel oxidation in simulation of complex combustion phenomena. There exist a few systematic methodologies to reduce detailed chemical mechanisms to smaller sizes involving less computational load. This research work concerns generation of a skeletal chemical mechanism by a directed relation graph with specified accuracy requirement. Two sequential stages for mechanism reduction are followed in a perfectly stirred reactor(PSR) for high temperature chemistry and to consider the autoignition delay time for low and high temperature chemistry. Reduction was performed for the detailed chemical mechanism of n-heptane consisting of 561 species and 2539 elementary reaction steps. Validation results show acceptable agreement for the autoignition delay time and the PSR calculation in wide parametric ranges of pressure, temperature and equivalence ratio.

• Kyungpook Mathematical Journal
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• v.60 no.3
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• pp.467-475
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• 2020

Let G be a chemical graph with vertex set {v₁, v₁, …, v_n} and degree sequence d(G) = (deg_G(v₁), deg_G(v₂), …, deg_G(v_n)). The inverse degree, R(G) of G is defined as $R(G)={\sum{_{i=1}^{n}}}\;{\frac{1}{deg_G(v_i)}}$. The cyclomatic number of G is defined as γ = m - n + k, where m, n and k are the number of edges, vertices and components of G, respectively. In this paper, some upper bounds on the diameter of a chemical graph in terms of its inverse degree are given. We also obtain an ordering of connected chemical graphs with respect to the inverse degree.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1004-1008
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• 1990

This research focuses on developing a new and computationally efficient algorithm for free space structuring and planning collision free paths for an autonomous mobile robot working in an environment populated with polygonal obstacles. The algorithm constructs the available free space between obstacles in terms of free convex area. A collision free path can be efficiently generated based on a graph constructed using the midpoints of common free links between free convex area as passing points. These points correspond to nodes in a graph and the connection between them within each convex area as arcs in this graph. The complexity of the search for collision free path is greatly reduced by minimizing the size of the graph to be searched concerning the number of nodes and the number of arcs connecting them. The analysis of the proposed algorithm shows its efficiency in terms of computation ability, safety and optimality.

• Journal of the Chungcheong Mathematical Society
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• v.35 no.3
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• pp.205-225
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• 2022

In this paper, we derive analytical closed results for the first (a, b)-KA index, the Sombor index, the modified Sombor index, the first reduced (a, b)-KA index, the reduced Sombor index, the reduced modified Sombor index, the second reduced (a, b)-KA index and the mean Sombor index mSO_α for the OTIS biswapped networks by considering basis graphs as path, wheel graph, complete bipartite graph and r-regular graphs. Network theory plays a significant role in electronic and electrical engineering, such as signal processing, networking, communication theory, and so on. A topological index (TI) is a real number associated with graph networks that correlates chemical networks with a variety of physical and chemical properties as well as chemical reactivity. The Optical Transpose Interconnection System (OTIS) network has recently received increased interest due to its potential uses in parallel and distributed systems.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.267-271
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• 2005

The goal of data mining is to extract new and useful knowledge from large scale datasets. As the amount of available data grows explosively, it became vitally important to develop faster data mining algorithms for various types of data. Recently, an interest in developing data mining algorithms that operate on graphs has been increased. Especially, mining frequent patterns from structured data such as graphs has been concerned by many research groups. A graph is a highly adaptable representation scheme that used in many domains including chemistry, bioinformatics and physics. For example, the chemical structure of a given substance can be modelled by an undirected labelled graph in which each node corresponds to an atom and each edge corresponds to a chemical bond between atoms. Internet can also be modelled as a directed graph in which each node corresponds to an web site and each edge corresponds to a hypertext link between web sites. Notably in bioinformatics area, various kinds of newly discovered data such as gene regulation networks or protein interaction networks could be modelled as graphs. There have been a number of attempts to find useful knowledge from these graph structured data. One of the most powerful analysis tool for graph structured data is frequent subgraph analysis. Recurring patterns in graph data can provide incomparable insights into that graph data. However, to find recurring subgraphs is extremely expensive in computational side. At the core of the problem, there are two computationally challenging problems. 1) Subgraph isomorphism and 2) Enumeration of subgraphs. Problems related to the former are subgraph isomorphism problem (Is graph A contains graph B?) and graph isomorphism problem(Are two graphs A and B the same or not?). Even these simplified versions of the subgraph mining problem are known to be NP-complete or Polymorphism-complete and no polynomial time algorithm has been existed so far. The later is also a difficult problem. We should generate all of 2$^n$ subgraphs if there is no constraint where n is the number of vertices of the input graph. In order to find frequent subgraphs from larger graph database, it is essential to give appropriate constraint to the subgraphs to find. Most of the current approaches are focus on the frequencies of a subgraph: the higher the frequency of a graph is, the more attentions should be given to that graph. Recently, several algorithms which use level by level approaches to find frequent subgraphs have been developed. Some of the recently emerging applications suggest that other constraints such as connectivity also could be useful in mining subgraphs : more strongly connected parts of a graph are more informative. If we restrict the set of subgraphs to mine to more strongly connected parts, its computational complexity could be decreased significantly. In this paper, we present an efficient algorithm to mine frequent subgraphs that are more strongly connected. Experimental study shows that the algorithm is scaling to larger graphs which have more than ten thousand vertices.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.228-233
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• 2005

The protein side-chain packing problem (SCPP) is known to be NP-complete. Various graph theoretic based side-chain packing algorithms have been proposed. However as the size of the protein becomes larger, the sampling space increases exponentially. Hence, one approach to cope with the time complexity is to decompose the graph of the protein into smaller subgraphs. Some existing approaches decompose the graph into biconnected components at an articulation point (resulting in an at-most 21-residue subgraph) or solve the SCPP by tree decomposition (4-, 5-residue subgraph). In this regard, we had also presented a deterministic based approach called as SPWCQ using the notion of maximum edge weight clique in which we reduce SCPP to a graph and then obtain the maximum edge-weight clique of the obtained graph. This algorithm performs well for a protein of less than 500 residues. However, it fails to produce a feasible solution for larger proteins because of the size of the search space. In this paper, we present a new heuristic approach for the side-chain packing problem based on the maximum edge-weight clique finding algorithm that enables us to compute the side-chain packing of much larger proteins. Our new approach can compute side-chain packing of a protein of 874 residues with an RMSD of 1.423${\AA}$.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2162-2176
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• 2018

Chemical reactions have an intricate relationship with the search for better-quality neighborhood solutions to optimization problems. A catalytic reaction for chemical reactions provides a clue and a framework to solve complicated optimization problems. The application of a catalytic reaction reveals new information hidden in the optimization problem and provides a non-intuitive perspective. This paper proposes a new simulated catalytic reaction method for search in optimization problems. In the experiments using this method, significantly improved results are obtained in almost all graphs tested by applying to a graph bisection problem, which is a representative problem of combinatorial optimization problems.