• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.220-222
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• 2006

This paper presents intelligent digital redesign method of global approach for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent the complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated lineal operators to be matched. Also, by using the bilinear and inverse bilinear approximation method, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs). Finally, a T-S fuzzy model for the chaotic Lorentz system is used as an example to guarantee the stability and effectiveness of the proposed method.

• Journal of Information Processing Systems
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• v.7 no.3
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• pp.447-458
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• 2011

This study presents a comprehensive solution to the collection management, which is based on the model for Cultural Objects (CCO). The developed system manages and spreads the collections that are safeguarded in museums and galleries more easily by using IT. In particular, we present our approach for a non-structured search and recovery of the objects based on the annotation of artwork images. In this methodology, we have introduced a faceted search used as a framework for multi-classification and for exploring/browsing complex information bases in a guided, yet unconstrained way, through a visual interface.

• Journal of Information Technology Applications and Management
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• v.23 no.4
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• pp.71-82
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• 2016

The purpose of this study is to prove empirically that technology investment propency factors (TIPFs) refect on the technological competitive advantage (TCA) and management performance. It includes the role of open technology innovation (OTI) approach is mediate to TCA from technology investment propensity. Especially the three TIPFs are market orientation, innovation orientation and strategy orientation. The analysis were performed based on the respondents' data from 181 firms focusing to technology innovation and information technology. The suggested research assumptions including structured equation model were proved. Therefore, this study emphasizes that CEO or CTO must concentrate on innovative, strategic and market oriented propensity when he makes a decision on technology investment. An open innovation approach is effective for getting high TCA and management performance in technology intensive firms such as technology innovation and information technology.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.496-498
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• 2005

This paper presents intelligent digital redesign method of global approach for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent the complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated linear operators to be matched. Also by using the power series, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs).

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.1
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• pp.77-94
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• 1997

Reengineering, also known as a business process redesign, involves a fundamental rethinking, and often a radical redesign, of an entire business process or a set of process to achieve dramatic improvements. The central paradox of reengineering is that its own advantages constitute the greatest threat to its success. For reengineering to be the right choice, the organization must have real capacities to embrace changes across the board. The key is to begin with, and to preserve, a vision of the new order, which drives this structured approach, and is in turn calibrated by that approach. However, in most cases of these calibrations, the empirical evidences on the effect of determinants in the reengineering are required. Seemingly, the research results in this area are scarcely verified. This article tried to search the effect of four dimensions of the reengineering toward the performance of reengineering. The results showed that the factors of the organization behavior and of the methodology/operation had more affected on the performance.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.205-210
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• 2004

This paper deals with rule extraction from data using rough set theory. We construct the rule base in a hierarchical granulation structure by applying core as a classification criteria at each level. When more than one core exist, the coverage is used for the selection of an appropriate one among them to increase the classification rate and accuracy. In Addition, a probabilistic approach is suggested so that the partially useful information included in inconsistent data can be contributed to knowledge reduction in order to decrease the effect of the uncertainty or vagueness of data. As a result, the proposed method yields more proper and efficient rule base in compatability and size. The simulation result shows that it gives a good performance in spite of very simple rules and short conditionals.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.4
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• pp.1237-1255
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• 2014

In wireless sensor networks (WSNs), hierarchical clustering is an efficient approach for lower energy consumption and extended network lifetime. In cluster-based multi-hop communications, a cluster head (CH) closer to the sink is loaded heavier than those CHs farther away from the sink. In order to balance the energy consumption among CHs, we development a novel cluster-based routing protocol for corona-structured wireless sensor networks. Based on the relaying traffic of each CH conveys, adequate radius for each corona can be determined through nearly balanced energy depletion analysis, which leads to balanced energy consumption among CHs. Simulation results demonstrate that our clustering approach effectively improves the network lifetime, residual energy and reduces the number of CH rotations in comparison with the MLCRA protocols.

• Journal of Information Science Theory and Practice
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• v.1 no.1
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• pp.10-26
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• 2013

Domain transfer is a widely recognized problem for machine learning algorithms because models built upon one data domain generally do not perform well in another data domain. This is especially a challenge for tasks such as opinion classification, which often has to deal with insufficient quantities of labeled data. This study investigates the feasibility of self-training in dealing with the domain transfer problem in opinion classification via leveraging labeled data in non-target data domain(s) and unlabeled data in the target-domain. Specifically, self-training is evaluated for effectiveness in sparse data situations and feasibility for domain adaptation in opinion classification. Three types of Web content are tested: edited news articles, semi-structured movie reviews, and the informal and unstructured content of the blogosphere. Findings of this study suggest that, when there are limited labeled data, self-training is a promising approach for opinion classification, although the contributions vary across data domains. Significant improvement was demonstrated for the most challenging data domain-the blogosphere-when a domain transfer-based self-training strategy was implemented.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.3
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• pp.254-262
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• 2008

In this paper, we propose an adaptive neural dynamic surface control (DSC) approach with $H_{\infty}$ tracking performance for full dynamics of nonlinear flight systems. It is assumed that the model uncertainties such as structured and unstrutured uncertainties, and external disturbances influence the nonlinear aircraft model. In our control system, self recurrent wavelet neural networks (SRWNNs) are used to compensate the model uncertainties of nonlinear flight systems, and an adaptive DSC technique is extended for the disturbance attenuation of nonlinear flight systems. All weights of SRWNNs are trained on-line by the smooth projection algorithm. From Lyapunov stability theorem, it is shown that $H_{\infty}$ performance nom external disturbances can be obtained. Finally, we present the simulation results for a nonlinear six-degree-of-freedom F-16 aircraft model to confirm the effectiveness of the proposed control system.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.7
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• pp.916-923
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• 2000

Numerical study of three-dimensional turbulent flow in a forward curved centrifugal fan is presented. Standard $k-{\varepsilon}$ turbulence model and non-orthogonal curvilinear coordinates arc used to consider the turbulent flow field and complex geometry. Finite Volume approach is adopted for discretization scheme and structured grid system is used to help convergence. Multiblock grid system is used for flow field and divided into five domains that are inlet, outlet, impeller, tip clearance and scroll. It is assumed that the flow field is steady and incompressible. These numerical results are compared with the experimental data inside a rotor and at the fan outlet. Most important flow features are captured through this numerical approach. Finally details of flow field inside a fan are described and analyzed.