• International conference on construction engineering and project management
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• 2015.10a
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• pp.620-621
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• 2015

In this study, the multi-criteria decision-making model based on Quality Function Deployment Method is proposed. Multicriteria decision-making is an attempt to link QFD method with the TOPSIS. By this effort, a model that makes client's decision-making more rational and objective in design phase is suggested. The multi-criteria decisionmaking model confirming to the Owner's requirements will improve the productivity of the construction industry and the satisfaction of the customer. Further study extending the range of the requirements, not only the Owner's requirement will be necessary to cover the various factors as much as possible. And then, finally as a flexible platform to achieve a sustainable quality management, web-based multi-criteria decision-making model can be utilized by the relevant stakeholders simultaneously with the feed-back and sharing the necessary informations.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.1
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• pp.135-142
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• 2012

In this paper, we proposed a new architecture called radial basis function-based polynomial neural networks classifier that consists of heterogeneous neural networks such as radial basis function neural networks and polynomial neural networks. The underlying architecture of the proposed model equals to polynomial neural networks(PNNs) while polynomial neurons in PNNs are composed of Fuzzy-c means-based radial basis function neural networks(FCM-based RBFNNs) instead of the conventional polynomial function. We consider PNNs to find the optimal local models and use RBFNNs to cover the high dimensionality problems. Also, in the hidden layer of RBFNNs, FCM algorithm is used to produce some clusters based on the similarity of given dataset. The proposed model depends on some parameters such as the number of input variables in PNNs, the number of clusters and fuzzification coefficient in FCM and polynomial type in RBFNNs. A multiobjective particle swarm optimization using crowding distance (MoPSO-CD) is exploited in order to carry out both structural and parametric optimization of the proposed networks. MoPSO is introduced for not only the performance of model but also complexity and interpretability. The usefulness of the proposed model as a classifier is evaluated with the aid of some benchmark datasets such as iris and liver.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.1
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• pp.21-31
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• 2002

This study applied each Neural Networks theory and Fuzzy Set theory to improve accuracy in remotely sensed images. Remotely sensed data have been used to map land cover. The accuracy is dependent on a range of factors related to the data set and methods used. Thus, the accuracy of maps derived from conventional supervised image classification techniques is a function of factors related to the training, allocation, and testing stages of the classification. Conventional image classification techniques assume that all the pixels within the image are pure. That is, that they represent an area of homogeneous cover of a single land-cover class. But, this assumption is often untenable with pixels of mixed land-cover composition abundant in an image. Mixed pixels are a major problem in land-cover mapping applications. For each pixel, the strengths of class membership derived in the classification may be related to its land-cover composition. Fuzzy classification techniques are the concept of a pixel having a degree of membership to all classes is fundamental to fuzzy-sets-based techniques. A major problem with the fuzzy-sets and probabilistic methods is that they are slow and computational demanding. For analyzing large data sets and rapid processing, alterative techniques are required. One particularly attractive approach is the use of artificial neural networks. These are non-parametric techniques which have been shown to generally be capable of classifying data as or more accurately than conventional classifiers. An artificial neural networks, once trained, may classify data extremely rapidly as the classification process may be reduced to the solution of a large number of extremely simple calculations which may be performed in parallel.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2002.11a
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• pp.109-112
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• 2002

So far, the closed-form Green's functions have been derived almost for th open microstrip structures. In the present study, closed-form Green's functions for a top-covered microstrip structure are derived. And an effect of top-cover is discussed in comparison with open structure.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.885-888
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• 1999

Radiation characteristics of axial elementary current source on the cylindrical bianisotropic substrateloaded with bianisotropic superstrate layer are presented. The effects of bianisotropic superstrate cover on the radiation problems of a microstrip antenna are studied. This investigation is performed by using the Green function formulation in the spectral domain. Numerical results for the radiation pattern of the bianisotropic superstrate-loaded microstrip antenna is analyzed.

• Journal of the Korean Mathematical Society
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• v.45 no.1
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• pp.221-228
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• 2008

In this paper, we study the complexity of semigroup actions using complexity functions of open covers. The main results are as follows: (1) A dynamical system is equicontinuous if and only if any open cover has bounded complexity; (2) Weak-mixing implies scattering; (3) We get a criterion for the scattering property.

• Archives of Craniofacial Surgery
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• v.21 no.3
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• pp.143-155
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• 2020

Surgical anatomy for Asian rhinoplasty Part I reviewed layered anatomy with neurovascular system of the nose. Part II discusses upper two-thirds of nose which consists of nasal bony and cartilaginous structures. Nasal physiology is mentioned briefly since there are several key structures that are important in nasal function. Following Part III will cover lower one-third of nose including in-depth anatomic structures which are important for advanced Asian rhinoplasty.

• Kyungpook Mathematical Journal
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• v.28 no.1
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• pp.79-82
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• 1988

This paper investigates the relationship between compactness and pseudo-compactness in subsets of C(X) where X is locally compact and first countable. Two primary theorems are proven. First, equicontinuity at a point is proven to be equivalent to the existence of a certain open cover of a pseudo-compact subset of C(X). The second theorem proves the equivalence of compactness and pseudo-compctness for closed subsets F of C(X).

• Kyungpook Mathematical Journal
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• v.46 no.2
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• pp.189-200
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• 2006

The semicontinuous quasi-uniformity is known to be one of the most important examples of transitive quasi-uniformities. The aim of this paper is to show that various facts in classical topology connected with the semicontinuous quasi-uniformity and semicontinuous real functions may be easily extended to pointfree topology via a construction introduced by the authors in a previous paper. Several consequences are derived.

• Fire Science and Engineering
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• v.33 no.6
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• pp.20-27
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• 2019

In this study, a new function with higher accuracy for fire heat release rate prediction was developed. The 'αt²' curve, which is the major exponential function currently used for fire engineering calculations, must be improved to minimize the prediction gap that causes fire system engineering inefficiency and lower cost-effectiveness. The newly developed prediction function was designed to cover the initial fire stage that features rapid growth based on logistic function theory, which has a more logical background and graphical similarity compared to conventional exponential function methods for 'αt²'. The new function developed in this study showed apparently higher prediction accuracy over wider range of fire growth durations. With the progress of fire growth pattern studies, the results presented herein will contribute towards more effective fire protection engineering.