• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.07a
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• pp.259-262
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• 2003

The surface electronic state of rutile $TiO_2$, which is an oxide semiconductor and has a wide band gap of 3.1 $\sim$ 3.5 eV, was calculated by DV-$X_{\alpha}$ method, which is a sort of the first principle molecular orbital method and uses Hartre-Fock-Slater approximation. The $[Ti_{15}O_{56}]^{-52}$ cluster model was used for the calculation of bulk state and the $[OTi_{11}O_{34}]^{-24}$ model for the surface state calculation. After calculations, the energy level diagrams and the deformation electron density distribution map were compared in both models. As results, it was identified that the surface energy levels are found between the valence and conduction band of bulk $TiO_2$ on the surface area. The energy values of these surface-induced levels are lower than conduction band of bulk $TiO_2$ by 0.1 $\sim$ 1 eV. From this fact, it is expected that the surface energy levels act as donar levels in n-type semiconductor.

• Proceedings of the KIEE Conference
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• 2002.07c
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• pp.1515-1517
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• 2002

$MnO_2$ is used for the oxide electrode of electrochemical equipments because of its good electric conductivity and low oxygen overpotential. The effect of additives on the properties of $MnO_2$ has been investigated to enhance the electric conductivity and the stability in an acid solution. In this research, the effect of Ni addition on ${\beta}-MnO_2$ was studied by the theoretical quantum chemical method. The calculation was carried out by the discrete variation $X{\alpha}$ method, which is a sort of the first principle method and use Hatre-Fock-Slater approximation. The electron energy level, the density of state, the bond overlap population, the charge density distribution and the net ionic transfer between cations and anions were calculated and discussed. The used cluster model was $(Mn_{10}NiO_{44})^{-44}$.

• Korean Journal of Crystallography
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• v.14 no.1
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• pp.16-23
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• 2003

The electronic structure and chemical bonding of β-MnO₂ were theoretically investigated by DV-X/sub α/ (the discrete variation X/sub α/) method. which is a sort of the first principle molecular orbital method using Hatre-Fock-Slater approximation. The calculations on several cluster models having different sizes were carried out for the determination of a model suited for analyzing bulk state. The Mn/sub 15/O/sub 56/ model was selected as a sufficiently suitable model for the calculation of electronic state and chemical bonding by the comparison of the calculated XPS (X-ray photo-electron spectrum) and experimentally measured XPS. By using this model, the electron energy level, the density of state, the bond overlap population, the charge density distribution, and the net ionic transfer between cations and anions were calculated and discussed.

• Journal of Digital Convergence
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• v.11 no.11
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• pp.343-349
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• 2013

Rough set theory comes to derive optimal rules through the effective selection of features from the redundancy of lots of information in data mining using the concept of equivalence relation and approximation space in rough set. The reduction of attributes is one of the most important parts in its applications of rough set. This paper purports to define a information-theoretic measure for determining the most important attribute within the association of attributes using rough entropy. The proposed method generates the effective reduct set and formulates the core of the attribute set through the elimination of the redundant attributes. Subsequently, the control rules are generated with a subset of feature which retain the accuracy of the original features through the reduction.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.77.2-77.2
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• 2012

We have studied the physical properties of X-ray point sources in galaxy clusters for years based on the archival observations using the most sophisticated space X-ray observatory, Chandra X-ray Observatory. Because the ultimate goal of the study is comparing the physical properties of X-ray point sources found in galaxy clusters to those in X-ray blank fields; blank fields are the regions in the sky where any noticeable cosmic diffuse X-ray emission is not observed, an important key issue regarding this study is picking out the point sources related with galaxy clusters. However we do not have red-shift information of all the X-ray point sources. Therefore as a first order approximation we will consider the point sources with smaller projected cluster-centric distance than the adopted size of galaxy clusters. As a first step of this study we perform X-ray surface photometry of ~600 galaxy clusters based on ~800 Chandra ACIS observations. We carefully investigate the radial structures of diffuse X-ray emission in 3 different energy bands. Based on the highly accurate surface photometry we determine the characteristic size of diffuse X-ray emission (i.e., the boundary of X-ray emission). We also investigate the cosmological evolution of this characteristic size of galaxy clusters. General discussion regarding the two dimensional morphology of galaxy clusters will be presented.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.11a
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• pp.99-102
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• 2003

The electronic structure of ${\beta}-MnO_2$ having impurities in the site of Mn was theoretically investigated by $DV-X_{\alpha}$ (the discrete variation $X{\alpha}$) method, which is a sort of the first principle molecular orbital method using Hatre-Fock-Slater approximation. The used cluster model was $[Mn_{14}MO_{56}]^{-52}$ (M = transient metals). Madelung potential and spin polarization were considered for more exact calculations. As results of calculations, the energy levels of all electron included in the model were obtained. The energy band gap and positions of impurity levies were discussed in association with impurity 34 orbital that seriously affect electrical properties of $MnO_2$. It was shown that the energy band gap decreased with the increase of the atomic number of transient metal impurity.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.07a
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• pp.309-312
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• 2004

The electronic structure of ZnO oxide semiconductor having high optical transparency and good electric conductivity was theoretically investigated by $DV-X_{\alpha}$(the discrete variation $X_{\alpha}$) method, which is a sort of the first principle molecular orbital method using Hatre-Fock-Slater approximation. The electrical and optical properties of ZnO are seriously affected by the addition of impurities. The imnurities are added to ZnO in order to increase the electric conductivity of an electrode without losing optical transparency. In this study, the effect of impurities of III and IV family on the band structure, impurity levels and the density of state of ZnO were investigated. The cluster model used for calculations was $[MZn_{50}O_{53}]^{-2}$(M=elements belonging to III and IV family).

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.1
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• pp.59-65
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• 2005

This paper proposes a novel TSK fuzzy modeling algorithm. Various approaches to fuzzy modeling when noise or outliers exist in the data have been presented but they are approaches to degrade effects of outliers or large noise by using loss function in the cost function mainly. The proposed algorithm is the modified version of noise clustering algorithm, and it adopts the method that does not use loss function, but method to cluster noise in a class. Noise clustering is a prototype-based clustering algorithm and it has no capability to regress. It conducts clustering of data first, and then conducts fuzzy regression. There are many algorithms to obtain parameters of premise and consequent part simultaneously, but they need to adapt the parameters obtained for more accurate approximation. In this paper, fuzzy regression is conducted with clustering by modifying noise clustering algorithm. We propose the algorithm that parameters of the premise part and the consequent part are obtained simultaneously, and the parameters obtained are not needed to adapt. We verify the proposed algorithm through simple examples and evaluate the test results compared with existing algorithms. The proposed algorithm shows robust performance against noise and it is easy to implement.

• Journal of Information Processing Systems
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• v.9 no.4
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• pp.633-650
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• 2013

All the imputation techniques proposed so far in literature for data imputation are offline techniques as they require a number of iterations to learn the characteristics of data during training and they also consume a lot of computational time. Hence, these techniques are not suitable for applications that require the imputation to be performed on demand and near real-time. The paper proposes a computational intelligence based architecture for online data imputation and extended versions of an existing offline data imputation method as well. The proposed online imputation technique has 2 stages. In stage 1, Evolving Clustering Method (ECM) is used to replace the missing values with cluster centers, as part of the local learning strategy. Stage 2 refines the resultant approximate values using a General Regression Neural Network (GRNN) as part of the global approximation strategy. We also propose extended versions of an existing offline imputation technique. The offline imputation techniques employ K-Means or K-Medoids and Multi Layer Perceptron (MLP)or GRNN in Stage-1and Stage-2respectively. Several experiments were conducted on 8benchmark datasets and 4 bank related datasets to assess the effectiveness of the proposed online and offline imputation techniques. In terms of Mean Absolute Percentage Error (MAPE), the results indicate that the difference between the proposed best offline imputation method viz., K-Medoids+GRNN and the proposed online imputation method viz., ECM+GRNN is statistically insignificant at a 1% level of significance. Consequently, the proposed online technique, being less expensive and faster, can be employed for imputation instead of the existing and proposed offline imputation techniques. This is the significant outcome of the study. Furthermore, GRNN in stage-2 uniformly reduced MAPE values in both offline and online imputation methods on all datasets.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.17 no.7
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• pp.691-696
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• 2004

The electronic state and chemical bonding of $\beta$-MnO$_2$ with transition metal dopants were theoretically investigated by DV-X$_{\alpha}$ (the discrete variational X$_{\alpha}$) method, which is a sort of the first principles molecular orbital method using the Hartree-Fock-Slater approximation. The calculations were performed with a $_Mn_{14}$ MO$_{56}$ )$^{-52}$ (M = transition metals) cluster model. The electron energy level, the density of states (DOS), the overlap population, the charge density distribution, and the net charges, were calculated. The energy level diagram of MnO$_2$ shows the different band structure and electron occupancy between the up spin states and down spin states. The dopant levels decrease between the conduction band and the valence band with the increase of the atomic number of dopants. The covalency of chemical bonding was shown to increase and ionicity decreased in increasing the atomic number of dopants. Calculated results were discussed on the basis of the interaction between transition metal 3d and oxygen 2p orbital. In conclusion it is expected that when the transition metals are added to MnO$_2$ the band gap decreases and the electronic conductivity increases with the increase of the atomic number of dopants. the atomic number of dopants.