• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.2
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• pp.399-407
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• 1998

This paper deals with a method for finding the physical structure of dynamic systems which shows reasonable response to a given specifiation. The method uses only four basic models of bond graph prototypes which have been originally proposed by the authors as a general model for dynamic systems, and then makes its procedure highly physical in the sense that it can synthesize a dynamic system through the structural transformation directly on bond graph models without any mathematical manipulation. Also, it is shown that this method has further advantages in optimizing parameters for an existing system rather than developing design concepts for a new device, the latter being more suitable using the so-called analytical synthesis method introduced by Park and Redfield. One example serves to trace the outlines of the direct synthesis method proposed in this paper for dynamic systems in terms of bond graph prototypes.

• Journal of the Society of Naval Architects of Korea
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• v.61 no.1
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• pp.19-28
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• 2024

Environmental regulations are becoming more stringent in response to climate change, especially concerning marine pollution caused by ship emissions. Large ships are adjusting by integrating technologies to reduce pollutant emissions and transitioning to eco-friendly fuels such as low-sulfur oil and LNG. However, small ships face space constraints for installing LNG propulsion systems and the risk of power depletion with pure electric propulsion. Consequently, there's growing interest in researching hybrid propulsion methods that combine electricity and diesel for smaller vessels. Hybrid propulsion systems utilize diverse energy sources, requiring an effective method for evaluating their efficiency. This study proposes employing Bond graph modeling to comprehensively analyze energy dynamics within hybrid propulsion systems, facilitating better understanding and optimization of their efficiency. Modeling of the ship's energy system using Bond graphs will be able to provide a framework for integrating various energy sources and evaluating their effects.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.323-326
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• 2005

This paper introduces design method for air pump system using bond graph and genetic programming to maximize outflow subject to a constraint specifying maximum power consumption. The air pump system is a mixed domain system which includes electromagnetic, mechanical and pneumaticelements. Therefore an appropriate approach for a better system for synthesis is required. Bond graphs are domain independent, allow free composition, and are efficient for classification and analysis of models, Genetic programming is well recognized as a powerful tool for open-ended search. The combination of these two powerful methods for evolution of multi-domain system, BG/GP, was tested for redesign of air pump system.

• Journal of Power Electronics
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• v.11 no.4
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• pp.439-448
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• 2011

In this work the Multi-Domain model of an electric vehicle is developed. The electric domain model consists on the traction drive and allows including faults associated with stator winding. The thermal model is based on a spatial discretization. It receives the power dissipated in the electric domain, it interacts with the environment and provides the temperature distribution in the induction motor. The mechanical model is a half vehicle model. Given that all models are obtained using the same approach (Bond Graph) their integration becomes straightforward. This complete model allows simulating the whole system dynamics and the analysis of electrical/mechanical/thermal interaction. First, experimental results are aimed to validate the proposed model. Then, simulation results illustrate the interaction between the different domains and highlight the capability of including faults.

• 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 Institute of Electrical and Electronic Material Engineers Conference
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• 2004.07a
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• pp.300-303
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• 2004

To fill the gap of films for metal-to-metal space High density plasma fluorinated silicate glass (HDP FSG) is used due to various advantages. However, FSG films can have critical drawbacks such as bonding issue of top metal at package, metal contamination, metal peel-off, and so on. These problems are generally caused by fluorine penetration out of FSG film. Hence, FSG capping layers such like SRO(Silicon Rich Oxide) are required to prevent flourine penetration. In this study, their characteristics and a capability to block fluorine penetration for various FSG capping layers are investigated through FTIR analysis. FTIR graphs of both SRO using ARC chamber and SiN show that clear Si-H bonds at $2175{\sim}2300cm^{-1}$. Thus, Si-H bond at $2175{\sim}2300cm^{-1}$ of FSG capping layers lays a key role to block fluorine penetration as well as dangling bond.

• Advances in nano research
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• v.13 no.2
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• pp.121-134
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• 2022

Emerge of nanotechnology impacts all aspects of humans' life. One of important aspects of the nanotechnology and nanoparticles (NPs) is in the food production industry. The safety of such foods is not well recognized and producing safe foods using nanoparticles involves delicate experiments. In this study, we aim to incorporate intelligent computer simulation in predicting safety degree of nanofoods. In this regard, the safety concerns on the nano-foods are addressed considering cytotoxicity levels in metal oxides nanoparticles using adaptive neuro-fuzzy inference system (ANFIS) and response surface method (RSM). Three descriptors including chemical bond length, lattice energy and enthalpy of formation gaseous cation of 15 selected NPs are examined to find their influence on the cytotoxicity of NPs. The most effective descriptor is selected using RSM method and dependency of the toxicity of these NPs on the descriptors are presented in 2D and 3D graphs obtained using ANFIS technique. A comprehensive parameters study is conducted to observe effects of different descriptors on cytotoxicity of NPs. The results indicated that combinations of descriptors have the most effects on the cytotoxicity.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.1
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• pp.101-108
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• 2008

This study is to examine bond strength of beam reinforced with GFRP rebar under 4-point fatigue bending test by adopting BRITISH STANDARD. The variables were made to have bonding length of 5times(5db), and 15times(15db) of the nominal diameter of GFRP rebar and were done to analyze the relationship between the bonding strength and the slip. In the result of the test, pull-out failure was dominant in the 5db specimen, patterns of the pull-out failure and concrete shear failure appeared in the 15db specimen showed only concrete shear failure at the end of bonding length. Therefore, The strain development consist of three different stage : A rapid increases form 0 to about 10% of total fatigue life. A uniform increases form 10% to about 70%~90%. Then a rapid increases until failure, if failure takes place. It seems that stress level has not influence on the secant modules of elasticity. And also according to the outcome the existing strengthening method came out to be the most superiority in S-N graphs.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.7
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• pp.135-144
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• 2022

The relationship between applying knowledge management and accepting environmentally managed accounting is more complicated than previous studies suggested. Knowledge management is both an antecedent and a consequence of implementing environmentally managed accounting in the workplace. Nonetheless, none of the prior studies have systematically investigated this relationship. The current article attempted to scrutinize the reciprocated multifaceted tie between environmental managerial accounting and knowledge management by utilizing the methods of directed graph searches as well as directed acyclic graphs. The research data was gathered from 342 publicly-listed corporations in Vietnam's key stock markets. The empirical findings disclose that implementing knowledge management can lead to adopting environmental managerial accounting in business, which is, in turn, an antecedent of accepting knowledge management. More importantly, the current research found that the adoption of knowledge management is the first factor to affect the research model. Nonetheless, the usage of knowledge management in business can, in turn, have a positive effect back to the implementing extent of environmental managerial accounting. The findings are beneficial to scientists and particularly to executives by shedding new insight into this reciprocated bond, which can lead executives to make sound decisions regarding knowledge management and environmental managerial accounting for businesses to acquire competitive advantages.

• Journal of KIISE:Databases
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• v.31 no.6
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• pp.641-649
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• 2004

The relationship between chemical structures and biological activities is researched briskly in the area of 'Medicinal Chemistry' At the base of these structure-based drug design tries, medicinal chemists search the existing drugs of similar chemical structure to target drug for the development of a new drug. Therefore, it is such necessary that an automatic system selects drug files that have a set of chemical moieties matching a user-defined query moiety. Substructure searching is the process of identifying a set of chemical moieties that match a specific query moiety. Testing for substructure searching was developed in the late 1950s. In graph theoretical terms, this problem corresponds to determining which graphs in a set are subgraph isomorphic to a specified query moiety. Testing for subgraph isomorphism has been proved, in the general case, to be an NP- complete problem. For the purpose of overcoming this difficulty, there were computational approaches. On the 1990s, a US patent has been granted on an atom-centered indexing scheme, used by the RS3 system; this has the virtue that the indexes generated can be searched by direct text comparison. This system is commercially used(http://www.acelrys.com/rs3). We define the RS3 system's drawback and present a new indexing scheme. The RS3 system treats substructure searching with substring matching by means of expressing chemical structure aspredefined strings. However, it has insufficient 'rerall' and 'precision‘ because it is impossible to index structures uniquely for same atom and same bond. To resolve this problem, we make the minimum-cost- spanning tree for one centered atom and describe a structure with paths per levels. Expressing 2D chemical structure into 1D a string has limit. Therefore, we break 2D chemical structure into 1D structure fragments. We present in this paper a new index technique to improve recall and precision surprisingly.