• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.3
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• pp.149-154
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• 2014

The cross-correntropy concept can be expressed with inner products of two different probability density functions constructed by Gaussian-kernel density estimation methods. Blind algorithms based on the maximization of the cross-correntropy (MCC) and a symbol set of randomly generated N samples yield superior learning performance, but have a huge computational complexity in the update process at the aim of weight adjustment based on the MCC. In this paper, a method of reducing the computational complexity of the MCC algorithm that calculates recursively the gradient of the cross-correntropy is proposed. The proposed method has only O(N) operations per iteration while the conventional MCC algorithms that calculate its gradients by a block processing method has $O(N^2)$. In the simulation results, the proposed method shows the same learning performance while reducing its heavy calculation burden significantly.

• The KIPS Transactions:PartB
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• v.16B no.5
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• pp.347-358
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• 2009

In this thesis, we develop a vision based hand motion recognition system using a camera with two rotational motors. Existing systems were implemented using a range camera or multiple cameras and have a limited working area. In contrast, we use an uncalibrated camera and get more wide working area by pan-tilt motion. Given an image sequence provided by the pan-tilt camera, color and pattern information are integrated into a tracking system in order to find the 2D position and direction of the hand. With these pose information, we estimate 3D motion plane on which the gesture motion trajectory from approximately forms. The 3D trajectory of the moving finger tip is projected into the motion plane, so that the resolving power of the linear gesture patterns is enhanced. We have tested the proposed approach in terms of the accuracy of trace angle and the dimension of the working volume.

• The Journal of the Acoustical Society of Korea
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• v.22 no.2
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• pp.145-152
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• 2003

In this paper, assuming that the score of speech utterance is the product of HMM log likelihood and HMM weight, we propose a new method that HMM weights are adapted iteratively like the general MCE training. The proposed method adjusts HMM weights for better performance using delta coefficient defined in terms of misclassification measure. Therefore, the parameter estimation and the Viterbi algorithms of conventional 1:.um can be easily applied to the proposed model by constraining the sum of HMM weights to the number of HMMs in an HMM set. Comparing with the general segmental MCE training approach, computing time decreases by reducing the number of parameters to estimate and avoiding gradient calculation through the optimal state sequence. To evaluate the performance of HMM-based speech recognizer by weighting HMM likelihood, we perform Korean isolated digit recognition experiments. The experimental results show better performance than the MCE algorithm with state weighting.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.3
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• pp.117-127
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• 1995

In this paper, we suggest a motion analysis method using ART-I1 competitive learning neural network and fuzzy reasoning by matching the same objects through the consecutive image sequence. we use the size and mean intensity of the region obtained from image segmentation for the region matching by the region and use a ART-I1 competitive learning neural network wh~ch has a learning ability to reflect the topology of the input patterns in order to select characteristic points to describe the shape of a region. Motion vectors for each regions are obtained by matching selected characteristic points. However, the two dimensional image, the projection of the the three dimensional real world, produces fuzziness in motion analysis due to its incompleteness by nature and the error from image segmentation used for extracting information about objects. Therefore, the belief degrees for each regions are calculated using fuzzy reasoning to l-nanipulate uncertainty in motion estimation.

• 전자공학회논문지 IE
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• v.43 no.2
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• pp.54-62
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• 2006

In this paper, a new stereo object tracking system using the disparity motion vector is proposed. In the proposed method, the time-sequential disparity motion vector can be estimated from the disparity vectors which are extracted from the sequence of the stereo input image pair and then using these disparity motion vectors, the area where the target object is located and its location coordinate are detected from the input stereo image. Basing on this location data of the target object, the pan/tilt embedded in the stereo camera system can be controlled and as a result, stereo tracking of the target object can be possible. From some experiments with the 2 frames of the stereo image pairs having $256\times256$ pixels, it is shown that the proposed stereo tracking system can adaptively track the target object with a low error ratio of about 3.05 % on average between the detected and actual location coordinates of the target object.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.360-362
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• 2002

Myocardial tagging technique such as spatial modulation of magnetization (SPAMM) allows the study of myocardial motion with high accuracy. Tagging contrast of such a tagging images can affect to the accuracy of the estimation of tag intersection in order to analyze the myocardial motion. Tagging contrast can be affected by tagline spacing. The aim of this study was to investigate the relationship between tagline spacing of SPAMM image and tagging contrast-to-noise ratio (CNR) experimentally. One healthy volunteer was undergone electrocardiographically triggered MR imaging with SPAMM-based tagging pulse sequence at a 1.5T MR scanner (Gyroscan Intera, Philips Medical System, Netherland). Horizontally modulated stripe patterns were imposed with a range from 3.6mm to 9.6mm of tagline spacing. Images of the left ventricle (LV) wall were acquired at the mid-ventricle level during cardiac cycle with FEEPI (TR/TE/FA=5.8/2.2/10). Tagging CNR for each image was calculated with a software which developed in our group. During contraction, tagging CNR was more rapidly decreased in case of short tagline spacing than in case of long tagline spacing. In the same heart phase, CNR was increased corresponding with tag line spacing. Especially, at the fully contracted heart phase, CNR was more rapidly increased than the other heart phases as a function of tagline spacing.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.5
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• pp.649-655
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• 2013

During welding, the dissimilar metal butt welds of nuclear piping are typically subjected to repair welding in order to eliminate defects that are found during post-weld inspection. It has been found that the repair weld can significantly increase the tensile residual stress in the weldment, and therefore, accurate estimation of the weld residual stress due to repair weld, especially for dissimilar metal welds using Ni-based alloy 82/182 in nuclear components, is of great importance in order to assess susceptibility to primary water stress corrosion cracking. In the present study, the stress distributions of dissimilar metal butt welds in nuclear reactor piping subjected to repair weld were investigated based on detailed nonlinear finite element analyses. Particular emphasis was placed on the variation of the stress distribution in the dissimilar metal butt weld according to the finite element welding analysis sequence for the repair welding process.

• The Journal of the Acoustical Society of Korea
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• v.14 no.5
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• pp.5-10
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• 1995

In this paper we present a clustering procedure based on the use of HMM in order to get multiple statistical models which can well absorb the variants of each speaker with different ways of saying words. The HMM-clustered models obtained from the developed technique are applied to the speaker independent isolated word recognition. The HMM clustering method splits off all observation sequences with poor likelihood scores which fall below threshold from the training set and create a new model out of the observation sequences in the new cluster. Clustering is iterated by classifying each observation sequence as belonging to the cluster whose model has the maximum likelihood score. If any clutter has changed from the previous iteration the model in that cluster is reestimated by using the Baum-Welch reestimation procedure. Therefore, this method is more efficient than the conventional template-based clustering technique due to the integration capability of the clustering procedure and the parameter estimation. Experimental data show that the HMM-based clustering procedure leads to $1.43\%$ performance improvements over the conventional template-based clustering method and $2.08\%$ improvements over the single HMM method for the case of recognition of the isolated korean digits.

• The Plant Pathology Journal
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• v.33 no.3
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• pp.296-306
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• 2017

Sugarcane mosaic virus (SCMV) is one of the most damaging viruses infecting sugarcane, maize and some other graminaceous species around the world. To investigate the genetic diversity of SCMV in Iran, the coat protein (CP) gene sequences of 23 SCMV isolates from different hosts were determined. The nucleotide sequence identity among Iranian isolates was more than 96%. They shared nucleotide identities of 75.5-99.9% with those of other SCMV isolates available in GenBank, the highest with the Egyptian isolate EGY7-1 (97.5-99.9%). The results of phylogenetic analysis suggested five divergent evolutionary lineages that did not completely reflect the geographical origin or host plant of the isolates. Population genetic analysis revealed greater between-group than within-group evolutionary divergence values, further supporting the results of the phylogenetic analysis. Our results indicated that natural selection might have contributed to the evolution of isolates belonging to the five identified SCMV groups, with infrequent genetic exchanges occurring between them. Phylogenetic analyses and the estimation of genetic distance indicated that Iranian isolates have low genetic diversity. No recombination was found in the CP cistron of Iranian isolates and the CP gene was under negative selection. These findings provide a comprehensive analysis of the population structure and driving forces for the evolution of SCMV with implications for global exchange of sugarcane germplasm. Gene flow, selection and somehow homologous recombination were found to be the important evolutionary factors shaping the genetic structure of SCMV populations.

• Tunnel and Underground Space
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• v.27 no.2
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• pp.109-119
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• 2017

A lot of twin tunnels were modelled with different pillar widths, rock mass classes and stress ratios in order to consider various site conditions, and the stabilities of the pillars were estimated by numerical analyses and scaled model tests. The strength-stress ratios of the pillar were obtained from three different methods which were using the stresses appeared at the middle point, the whole average and the left/right edges of the pillar. The strength-stress ratio of the pillar edges showed relatively conservative values among them, and it was also practically consistent with the tunnel excavating steps comprising the construction sequence analyses which included the partial excavation and the support system. Scaled model tests were also performed to investigate the tunnel stability, where it was found that cracks were progressively generated from the pillar edges toward the middle point of the pillar. Therefore, in order to both prevent the local damage of pillar and conservatively estimate the tunnel stability, it was thought to be an appropriate method using the strength-stress ratio obtained from the left/right edges of the pillar.