• Smart Structures and Systems
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• v.5 no.5
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• pp.507-515
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• 2009

The present work is an alternative methodology in order to balance a nonlinear highly flexible rotor by using neural networks. This procedure was developed aiming at improving the performance of classical balancing methods, which are developed in the context of linearity between acting forces and resulting displacements and are not well adapted to these situations. In this paper a fully experimental procedure using neural networks is implemented for dealing with the adaptive balancing of nonlinear rotors. The nonlinearity results from the large displacements measured due to the high flexibility of the foundation. A neural network based meta-model was developed to represent the system. The initialization of the learning procedure of the network is performed by using the influence coefficient method and the adaptive balancing strategy is prone to converge rapidly to a satisfactory solution. The methodology is tested successfully experimentally.

• Proceedings of the Korea Contents Association Conference
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• 2006.05a
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• pp.440-443
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• 2006

In this paper, we implemented design pattern retrieval system for efficient management and reusability of design patterns. Pattern is consisted of property information and meta information. Property information is used for similarity measurement on classification and retrieval of patterns. Meta information is used for UML modeling of patterns. We classified design patterns with the empirical scope in addition to Gamma's basic classification.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.5
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• pp.594-600
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• 2006

The optimization has been performed to search an economical running pattern in the view point of trip time and energy consumption. Fuzzy control model has been applied to build the meta-model. To identify the structure and its parameters of a fuzzy model, fuzzy c-means clustering method and differential evolutionary scheme ate utilized, respectively. As a result, two meta-models for trip time and energy consumption are constructed. The optimization to search an economical running pattern is achieved by differential evolutionary scheme. The result shows that the proposed methodology is very efficient and conveniently applicable to the operation of railway system.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.792-799
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• 2003

As eTransformation and collaborative eCommerce have been on the rise, business processes between business partners are increasingly recognized as important assets that need to be integrated. These trends imply more complex and dynamic business processes should be considered in order to integrate related business organizations and business units. Moreover, these business processes are widely distributed across stakeholders. Therefore, there is a need for business process modeling that is usable, flexible and capable of integrating systems consistently across businesses and technology barriers. In this paper, a business process modeling methodology is introduced, which is based on top­do\W and model-driven approach utilizing OMG's MDA(Model-Driven Architecture) and UML profile for EDOC(Enterprise Distributed Object Computing). This provides the ability to model business process at all levels simultaneously, to combine business process models retaining their meaning, to use business process design patterns constraining the behavior of sub-processes, and to derive specific codes from a stable model as the underlying infrastructure shifts over time. In addition, we suggest some modifications of the meta-model for EDOC-Business Process Profile by adding new features in order to model business processes rigidly. This paper illustrates some examples of business process modeling and compares them with UML diagrams and IDEF models. The proposed methodology is implemented to develop a business process modeling tool.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.308-313
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• 2016

Modern systems have become more and more complex due to the ever-increasing user requirements and rapid advance of technology. As such, the frequency of accidents due to system design errors or failure has been increasing. When the damage incurred by accidents to human beings or property is serious, the underlying systems are referred to as safety-critical systems. The development of such systems requires special efforts to ensure the safety of the human beings operating them. To cope with such a requirement, in this paper an approach is employed in which we consider safety starting from the conceptual design phase of the systems. Specifically, a systems design method that can detect functional failure is proposed by utilizing meta-models and M&S methods. To accomplish this, the safety design data from international safety standards are first extracted and also a meta-model is generated using SysML (systems modeling language). Then, a SysML-based system design method is proposed based on the use of the developed meta-model. We also discuss how the safety requirements can be created and verified using a simulation method. Finally, through a case study in automotive design, it is demonstrated that the detection of a functional failure and the verification of a safety requirement can be accomplished using the SysML-based M&S method. This study indicates that the use of meta-models can be useful for collecting and managing safety data and that the meta-model based M&S method can make it possible to satisfy the system requirements by reducing the design errors.

• Journal of Korea Multimedia Society
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• v.12 no.2
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• pp.231-243
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• 2009

Currently interests of embedded software in various areas such as automotive field, ship field, robot field is increasing according to expand market of embedded systems. Various researches such as embedded operating systems, embedded software modeling technique, embedded software testing, and so on are going in progress. However systematic engineering approach in embedded system development is poor because embedded areas focus on hardware parts until now. Furthermore, framework-based de sign technique considering reusability is not reflected in embedded system development. Those development results in many of dead codes scattered in system, and results in poor reusability of system. This paper suggests a framework of embedded system for reusability and a static meta-model for reuse framework. Proposed meta-model expresses not only the structure of reuse framework, but also allows a designer to extend and design easily models of embedded system based on reuse framework according to various embedded system types.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.378-381
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• 2012

Increasingly the frequency of use of mathematical modeling and computer simulation, in order to solve complex engineering problems in the field of Applied Science, the researchers need a simulation framework that can make their simulation-based research easier and more convenient. computer simulation framework is composed of various components such as preprocessor, solver, visualization program, computational resources and job scheduler. However until now, no standardized schema for the components of the simulation framework exist, so it is difficult to config that make a general-purpose simulation framework. In other words, most of the existing simulation framework is a structure that provides only limited functionality is dependent on the particular solver code. In this paper, we designed the meta-information schema that can be contained of a various solver code to be used for the simulation framework and we implemented the Web-based simulation environment using our meta-information schema.

• Clinical and Experimental Pediatrics
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• v.63 no.2
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• pp.34-43
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• 2020

Phenylketonuria is a disease caused by congenital defects in phenylalanine metabolism that leads to irreversible nerve cell damage. However, its detection in the early days of life can reduce its severity. Thus, many countries have started disease screening programs for neonates. The present study aimed to determine the worldwide prevalence of classic phenylketonuria using the data of neonatal screening studies.The PubMed, Web of Sciences, Sciences Direct, ProQuest, and Scopus databases were searched for related articles. Article quality was evaluated using the Joanna Briggs Institute Critical Appraisal Evaluation Checklist. A random effect was used to calculate the pooled prevalence, and a phenylketonuria prevalence per 100,000 neonates was reported. A total of 53 studies with 119,152,905 participants conducted in 1964-2017 were included in this systematic review. The highest prevalence (38.13) was reported in Turkey, while the lowest (0.3) in Thailand. A total of 46 studies were entered into the meta-analysis for pooled prevalence estimation. The overall worldwide prevalence of the disease is 6.002 per 100,000 neonates (95% confidence interval, 5.07-6.93). The meta-regression test showed high heterogeneity in the worldwide disease prevalence (I²=99%). Heterogeneity in the worldwide prevalence of phenylketonuria is high, possibly due to differences in factors affecting the disease, such as consanguineous marriages and genetic reserves in different countries, study performance, diagnostic tests, cutoff points, and sample size.

• Journal of Digital Convergence
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• v.17 no.11
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• pp.149-156
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• 2019

With widespread use of information technologies, information privacy issues have been gaining more attention by not only the public but also researchers. The number of studies on the issues has been increasing exponentially, which makes incomprehensible the whole picture of research outcome. Thus, it is necessary to conduct a systematic examination of past research. This study developed two competing models with four essential constructs in information privacy research and empirically tested the models with data obtained from previous studies. This study employed a quantitative meta-analysis method called TSSEM. It is one of MASEM methods in which structural equation modeling and meta-analysis are integrated. The analysis results indicated that risk-centric model exhibited much better model fits than those of concern-centric model. This study implies that traditional concern-centric model should be questioned it's explanatory power of the model and researchers may consider alternative risk-centric model to explain user's intention to provide privacy information.

• Structural Engineering and Mechanics
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• v.61 no.2
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• pp.283-293
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• 2017

The main contribution of the present paper is to propose an intelligent fuzzy inference system approach for modeling the debonding strength of masonry elements retrofitted with Fiber Reinforced Polymer (FRP). To achieve this, the hybrid of meta-heuristic optimization methods and adaptive-network-based fuzzy inference system (ANFIS) is implemented. In this study, particle swarm optimization with passive congregation (PSOPC) and real coded genetic algorithm (RCGA) are used to determine the best parameters of ANFIS from which better bond strength models in terms of modeling accuracy can be generated. To evaluate the accuracy of the proposed PSOPC-ANFIS and RCGA-ANFIS approaches, the numerical results are compared based on a database from laboratory testing results of 109 sub-assemblages. The statistical evaluation results demonstrate that PSOPC-ANFIS in comparison with ANFIS-RCGA considerably enhances the accuracy of the ANFIS approach. Furthermore, the comparison between the proposed approaches and other soft computing methods indicate that the approaches can effectively predict the debonding strength and that their modeling results outperform those based on the other methods.