• Korea-Australia Rheology Journal
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• v.18 no.2
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• pp.99-102
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• 2006

Primitive chain network model for block copolymers is used here to simulate molecular dynamics in the entangled state with acceptable computational cost. It was found that i) the hooking procedure rearranging the topology of the entangled network is critical for the equilibrium structure of the system, and ii) simulations accounting for the different chemistry, i.e., with a biased hooking probability based on interaction parameter ${\chi}$ for selection of the hooked partner, generates a reasonable phase diagram.

• Journal of the Korean Operations Research and Management Science Society
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• v.14 no.1
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• pp.88-96
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• 1989

General measure in the reliability is the k-terminal reliability, which is the probability that the specified vertices are connected by the working edges. To compute the k-terminal reliability components are usually assumed to be statistically independent. In this study the modeling and analysis of the k-terminal reliability are investigated when dependency among components is considered. As the size of the network increases, the number of the joint probability parameter to represent the dependency among components is increasing exponentially. To avoid such a difficulty the structured-event-based-reliability model (SERM) is presented. This model uses the combination of the network topology (physical representation) and reliability block diagram (logical representation). This enables us to represent the dependency among components in a network form. Computational algorithms for the k-terminal reliability in SERM are based on the factoring algorithm Two features of the ractoring algorithm are the reliability preserving reduction and the privoting edge selection strategy. The pivoting edge selction strategy is modified by two different ways to tackle the replicated edges occuring in SERM. Two algorithms are presented according to each modified pivoting strategy and illustrated by numerical example.

• The KIPS Transactions:PartA
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• v.17A no.4
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• pp.203-212
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• 2010

Recently, in automotive industry, there have been many researches related with hardware components and embedded software which controls hardware components. Since most of embedded software is tightly dependent on car manufacturers, there were some problems in reusability and interoperability of automotive software. In order to solve these problems, AUTOSAR standardized the component-based software architecture of automotive software. In AUTOSAR, several modeling diagrams should be described and their dependencies are also checked. Currently, a few company developed the prototypes of tools supporting AUTOSAR. In this paper, a component modeling tool based on AUTOSAR 3.0 is developed for enhancing the usability of existing tools using Eclipse GMF. The tool is composed of a graphical component modeling tool and a graphical network topology tool. Since these tools are generated based on GMF without hard coding, it is relatively easy to customize the tools for adopting company‘s needs and easy to follow the improvement of the standard and development environments.

• The KIPS Transactions:PartC
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• v.14C no.5
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• pp.453-462
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• 2007

NGN is a packet-based converged network to support session and non-session based services in QoS-enabled broadband transport technologies. Resource and admission control functions(RACF) of NGN have been considering COPS and SNMP as resource management protocols to collect network topology and resource status information of transport network. This paper defines requirements of resource management in NGN transport network, and proposes protocol independent information model to keep consistency of data models of each resource management protocol. Based on this information model described with UML class diagram, we designed and implemented NGN resource management system on Web Services.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.354-358
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• 2001

Cosim (Hardware and Software Co-Simulator) is a JavaBeans-based simulation tool fur validating systems architecture and estimating performance of web applications. Cosim has four components: Modeler, Translator, Engine and Scenario. Users start from Modeler to describe systems architecture in UML(Unified Modeling Language) deployment diagram, and then specify hardware & software performance parameters such as execution delay, network topology, and frame size. All information specified on Modeler are sent to Translator, and then automatically converted to Java programs. Scenario is responsible to run the Java program and produce results in text reports and graphs. Developers can reduce development time and cost by validating systems architecture of web applications before the actual deployment.

• Wind and Structures
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• v.39 no.1
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• pp.1-14
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• 2024

Widespread damages from extreme winds have attracted lots of attentions of the resilience assessment of power distribution systems. With many related environmental parameters as well as numerous power infrastructure components, such as poles and wires, the increased challenge of power asset management before, during and after extreme events have to be addressed to prevent possible cascading failures in the power distribution system. Many extreme winds from weather events, such as hurricanes, generate widespread damages in multiple areas such as the economy, social security, and infrastructure management. The livelihoods of residents in the impaired areas are devastated largely due to the paucity of vital utilities, such as electricity. To address the challenge of power grid asset management, power system clustering is needed to partition a complex power system into several stable clusters to prevent the cascading failure from happening. Traditionally, system clustering uses the Binary Decision Diagram (BDD) to derive the clustering result, which is time-consuming and inefficient. Meanwhile, the previous studies considering the weather hazards did not include any detailed weather-related meteorologic parameters which is not appropriate as the heterogeneity of the parameters could largely affect the system performance. Therefore, a fragility-based network hierarchical spectral clustering method is proposed. In the present paper, the fragility curve and surfaces for a power distribution subsystem are obtained first. The fragility of the subsystem under typical failure mechanisms is calculated as a function of wind speed and pole characteristic dimension (diameter or span length). Secondly, the proposed fragility-based hierarchical spectral clustering method (F-HSC) integrates the physics-based fragility analysis into Hierarchical Spectral Clustering (HSC) technique from graph theory to achieve the clustering result for the power distribution system under extreme weather events. From the results of vulnerability analysis, it could be seen that the system performance after clustering is better than before clustering. With the F-HSC method, the impact of the extreme weather events could be considered with topology to cluster different power distribution systems to prevent the system from experiencing power blackouts.