• Journal of Biomedical Engineering Research
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• v.8 no.2
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• pp.171-176
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• 1987

Wiener filtering method was applied to the dual energy imaging procedure in digital radiography(D.R.). A linear scanning photodiode arrays with 1024 elements(0.6mm H 1.3mm pixel size) were used to obtain chest images in 0.7 sec. For high energy image acquisition, X-ray tube was set at 140KVp, 100mA with a rare-earth phosphor screen. Low energy image was obtained with X-ray tube setting at 70KVp, 150mA. These measured dual energy images are represented in the vector matrix notation as a linear discrete model including the additive random noise. Then, the object images are restored in the minimum mean square error sense using Wiener filtering method in the transformed domain. These restored high and low energy images are used for computation of the basis image decomposition. Then the basis images are linearly combined to produce bone or tissue selective images. Using this process, we could improve the signal to noise ratio characteristics in the material selective images.

• Bulletin of the Korean Mathematical Society
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• v.46 no.5
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• pp.979-998
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• 2009

Involving the Ricci curvature and the squared mean curvature, we obtain a basic inequality for a submanifold of an S-space form tangent to structure vector fields. Equality cases are also discussed. As applications we find corresponding results for almost semi-invariant submanifolds, $\theta$-slant submanifolds, anti-invariant submanifold and invariant submanifolds. A necessary and sufficient condition for a totally umbilical invariant submanifold of an S-space form to be Einstein is obtained. The inequalities for scalar curvature and a Riemannian invariant $\Theta_k$ of different kind of submanifolds of a S-space form $\tilde{M}(c)$ are obtained.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.3
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• pp.221-227
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• 2020

In this paper, the Iterated Consider Extended Kalman Filter (ICEKF) is proposed for bearing-only localization of GNSS interference to improve the estimation performance and filter consistency. The ICEKF is an extended version of Consider KF (CKF) for Iterated EKF (IEKF) to consider an effect of bearing measurement bias error to filter covariance. The ICEKF can mitigate the EKF divergence problem which can occur when linearizing the nonlinear bearing measurement by a large initial state error. Also, it can mitigate filter inconsistency problem of EKF and IEKF which can occur when a weakly observable bearing measurement bias error state is not included in filter state vector. The simulation result shows that the localization error of the ICEKF is smaller than the EKF and IEKF, and the Root Mean Square (RMS) estimation error of ICEKF matches the covariance of filter.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.913-916
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• 1998

In this paper, to provide the robustness of character recognition, we propose a recognition method using the dilated boundary curve feature which has the invariance characteristics for the shift, scale, and rotation changes of character pattern. And its some characteristics and effectieness are evaluated through the experiments for both the english alphabets and the numeral digits. The feature vector is represented by the fourier descriptor for a boundary curve of the dilated character pattern which is generated by the circular mask dilation method, and is used for a nearest neighbort classifier(NNC) or a nearest neighbor mean classifier(NNMC). These the processing time and the recognition rate, and take also the robustness of recognition for both some internal noise and partial corruption of an image pattern.

• Journal of the Korean Data and Information Science Society
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• v.14 no.4
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• pp.1045-1053
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• 2003

Markovian EWMA control chart for simultaneously monitoring mean vector of the several correlated quality characteristics is investigated. Properties of multivariate Shewhart chart and EWMA chart are evaluated for matched FSI (fixed sampling interval) and VSI(variable sampling interval) scheme. We obtained VSI EWMA chart is more efficient than Shewhart chart for small or moderate shifts. And, we obtained stablized numerical results with Markov chain method when the number of transient state is greater than 100.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.9-11
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• 2005

We propose a new content-based image retrieval using a block color co-occurrence matrix (BCCM) and pattern correlogram. In the proposed method, the color feature vectors are extracted by using BCCM that represents the probability of the co-occurrence of two mean colors within blocks. Also the pattern feature vectors are extracted by using pattern correlogram which is combined with spatial correlation of pattern. In the proposed pattern correlogram method. after block-divided image is classified into 48 patterns with respect to the change of the RGB color of the image, joint probability between the same pattern from the surrounding blocks existing at the fixed distance and the center pattern is calculated. Experimental results show that the proposed method can outperform the conventional methods as regards the precision and the size of the feature vector dimension.

• Asia pacific journal of information systems
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• v.12 no.2
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• pp.179-195
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• 2002

In this research, we developed an efficient Hangul document classification system for text mining. We mean 'efficient' by maintaining an acceptable classification performance while taking shorter computing time. In our system, given a query document, k documents are first retrieved from the document case base using the k-nearest neighbor technique, which is the main algorithm of case-based reasoning. Then, TFIDF method, which is the traditional vector model in information retrieval technique, is applied to the query document and the k retrieved documents to classify the query document. We call this procedure 'CB_TFIDF' method. The result of our research showed that the classification accuracy of CB_TFIDF was similar to that of traditional TFIDF method. However, the average time for classifying one document decreased remarkably.

• 한국전산유체공학회:학술대회논문집
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• 2004.10a
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• pp.121-125
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• 2004

The preprocessor - solver - postprocessor software for 2D/Axisymmetric CSCM Upwind Flux Difference Splitting Navier-Stokes code has been developed for undergraduate educational purpose. This computational fluid dynamics (CFD) software allows students to setup, solve, visualize and control dynamically server for their own fluid problems via Internet. The preprocessor Is capable of generating geometry and grid, initial solution data and required solver control parameters. The postprocessor shows vector plot and contour plot with different options while residual plot shows root-mean-square (RMS) error history graphically and retrieves the data from solver interactively. Special feature of the preprocessor is grid generation part which is based on MFC/Visual C++ application and FORTRAN single block grid generator process. Many users can access solver via Internet from client computers and solve desired problems using locally installed pre- and postprocessor and remote powerful solver part.

• Proceedings of the KSME Conference
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• 2002.08a
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• pp.193-196
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• 2002

The relativistic theory has not been properly taken up by the marine hydrodynamicists. To take on a relativistic view, we confine ourselves to a simple vector case of a wave train in spacetime, to be shown to represent a sound wave or a surface wave, and bring in an observer who is travelling on another platform. We are interested in relative position of each event on these two worldlines. It, then, will be shown that the velocity, the acceleration, the encounter frequency, the group velocity, and the time and the space distance between the wave and the observer on the worldlines should all be derivable in principle. This is interpreted to mean that we really have the relativistic events taking place with different values of time dilation in the sense of 'spacetime', and that the well-known ${\lceil}special Theory of Relativity{\rfloor}$ applies just as well in hydrodynamic waves.

• MALSORI
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• no.53
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• pp.103-118
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• 2005

The performance of speech recognition system is degraded by mismatch between training and test environments. Recently, Stereo-based Piecewise LInear Compensation for Environments (SPLICE) was introduced to overcome environmental mismatch using stereo data. In this paper, we propose several methods to improve the conventional SPLICE and evaluate them in the Aurora2 task. We generalize SPLICE to compensate for covariance matrix as well as mean vector in the feature space, and thereby yielding the error rate reduction of 48.93%. We also employ the weighted sum of correction vectors using posterior probabilities of all Gaussians, and the error rate reduction of 48.62% is achieved. With the combination of the above two methods, the error rate is reduced by 49.61% from the Aurora2 baseline system.