• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1598-1601
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• 1987

This paper proposes a new set of topological features (primitives) for use with a syntactic recognizer for high-accuracy recognition of printed alphanumeric characters. The recognition is accomplished on nine character groups, where each group has different combinations of four feature points. A skeleton enhancement eliminating isolated points and smoothing irregular points is developed. The tree automata processed in parallel enables the realization of high-recognition speeds and font-type independent recognition. The proposed character recognition system is tested for alphanumeric character fonts of dot matrix printer and plotter using IBM-PC/XT.

• Proceedings of the KSRS Conference
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• v.1
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• pp.308-311
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• 2006

This study compared between tropospheric column ozone by applying the SAM method to TOMS and OMI data for northern summer. Tropospheric ozone from the SAM represents a peak over the tropical Atlantic, where it is related with biomass burning. This feature is also seen in the distribution of the model and CO. Additionally, enhancement of the SAM ozone over the Middle East, and South and North America agrees well with the model and CO distribution. However, the SAM results show more ozone than the model results over the northern hemisphere, especially the ocean (e.g. the North Pacific and the North Atlantic). The tropospheric ozone distribution from OMI data shows more ozone than that from TOMS data. This can be caused by different viewing angle, sampling frequency, and a-priori ozone profiles between OMI and TOMS. The correlation between the SAM tropospheric ozone and CO is better than that between the model and CO in the tropics. However, that correlation is reversed in the midlatitude.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.85-89
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• 2004

최근 몇 년 동안 사람들의 고유한 생리적인 특징을 이용한 생체 인식은 새로운 학문으로서 연구 및 개발이 활발하게 진행되고 있다. Hand-Geometry는 생체 인식의 확인 그리고 취득의 편리 때문에 식별 그리고 확인을 위하여 사용되고 있다. 그러므로, 본 논문은 이러한 특징을 가지는 손의 기하학적인 Hand-Geometry 인식 시스템을 제안하고자 한다. 해부학적인 관점에서, 인간의 손은 길이, 폭, 두께, 기하학적인 모양, 손바닥의 모양, 그리고 손가락들의 기하학적인 모양까지 특성으로 나타내어 질 수 있다. 그러나 특징 데이터 가운데 사용자의 Hand-GeoMetry의 특징에 따라 길이 데이터가 변하는 것을 실험적으로 발견하였다. 따라서 이와 같은 가변적인 길이 데이터를 안정화시키기 위하여 본 논문에서는 길이 데이터의 기준점을 손톱 아래 점으로 정하고, GA를 적용하여 보다 안정된 특징점을 추출하였다. 본 논문에서 제안한 Hand-Geometry 인식 시스템은 성인 20명의 개인에 대해 100개의 측정 데이터에 기인한 확인 결과를 제시한다. 인식 과정은 320$\times$240의 이미지로 실험하였고 인식 과정의 결과는 95 %의 적중률과 0.020의 FAR로 나타났다.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.07b
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• pp.1270-1273
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• 2004

The combination of methane-chemical activation and Self-propagating High-temperature synthesis (SHS) has widened the possibilities for both methods. For YBCO systems the investigation showed that a short-term mechano-chemical activation of initial powders before SHS leads to single-phase and ultra-fine products. A new technique for preparation ultra-fine high-temperature superconductors of YBCO composition with a grain size d < $1{\mu}m$ is developed. The specific feature of the technique is formation of the $YBa_2Cu_3O_{7-x}$ crystalline lattice directly from an X-ray amorphous state arising as a result of mechanical activation of the original oxide mixture. The technique allows the stage of formation of any intermediate reaction products to be ruled out. X-ray and magnetic studies of ultra-fine high temperature superconductors (HTS) are carried out. Dimension effects associated with the microstructure peculiarities are revealed. A considerable enhancement of inter-grain critical currents is found to take place in the ultra-fine samples investigated.

• Journal of Industrial Technology
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• v.15
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• pp.51-62
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• 1995

Databases can crash due to various failures in computer systems. Recovery is a mechanism for restoring consistent data from damages caused by the by the failures and is an essential feature in database systems. This paper surveys recovery techniques for memory resident database systems. We first describe the basic architecture for memory resident database systems, and point out the main factors affecting their performance enhancement. Next, we explain the write-ahead logging(WAL), a recovery technique widely-used in most disk resident database systems, for easy understanding of basic recovery mechanisms. And then, we discuss some new concepts employed in memory resident database systems recovery. Finally, we present a representative memory resident database recovery technique, which is based on a special purpose hardware called HALO, as a case study.

• The Journal of the Acoustical Society of Korea
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• v.17 no.4E
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• pp.3-10
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• 1998

This paper concerns the dynamical behavior, in probabilistic sense, of a feedforward neural network performing auto association for novelty. Networks of retinotopic topology having a one-to-one correspondence between and output units can be readily trained using back-propagation algorithm, to perform autoassociative mappings. A novelty filter is obtained by subtracting the network output from the input vector. Then the presentation of a "familiar" pattern tends to evoke a null response ; but any anomalous component is enhanced. Such a behavior exhibits a promising feature for enhancement of weak signals in additive noise. As an analysis of the novelty filtering, this paper shows that the probability density function of the weigh converges to Gaussian when the input time series is statistically characterized by nonsymmetrical probability density functions. After output units are locally linearized, the recursive relation for updating the weight of the neural network is converted into a first-order random differential equation. Based on this equation it is shown that the probability density function of the weight satisfies the Fokker-Planck equation. By solving the Fokker-Planck equation, it is found that the weight is Gaussian distributed with time dependent mean and variance.

• Proceedings of the KSME Conference
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• 2000.04b
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• pp.144-147
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• 2000

A numerical method for the solution of one-dimensional inverse heat conduction problem is established and its performance is demonstrated with computational results. The present work introduces the maximum entropy method in order to build a robust formulation of the inverse problem. The maximum entropy method finds the solution that maximizes the entropy functional under given temperature measurement. The philosophy of the method is to seek the most likely inverse solution. The maximum entropy method converts the inverse problem to a non-linear constrained optimization problem of which constraint is the statistical consistency between the measured temperature and the estimated temperature. The successive quadratic programming facilitates the maximum entropy estimation. The gradient required fur the optimization procedure is provided by solving the adjoint problem. The characteristic feature of the maximum entropy method is discussed with the illustrated results. The presented results show considerable resolution enhancement and bias reduction in comparison with the conventional methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.8C
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• pp.696-702
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• 2007

This paper proposes a regional feature preserving adaptive interpolation algorithm for natural images. The algorithm can be used in resolution enhancement, arbitrary rotation and other applications of still images. The basic idea is to first scan the sample image to initialize a 2D array which records the edge direction of all four-pixel squares, and then use the array to adapt the interpolation at a higher resolution based on the edge structures. A hybrid approach of switching between bilinear and triangulation-based interpolation is proposed to reduce the overall computational complexity. The experiments demonstrate our adaptive interpolation and show higher PSNR results of about max 2 dB than other traditional interpolation algorithms.

• Speech Sciences
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• v.11 no.2
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• pp.247-257
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• 2004

There has been many research efforts to overcome the problems of speech recognition in the noisy conditions. Among them, the model-based compensation methods such as the parallel model combination (PMC) and vector Taylor series (VTS) have been found to perform efficiently compared with the previous speech enhancement methods or the feature-based approaches. In this paper, a data-driven model compensation approach that adapts the HMM(hidden Markv model) parameters for the noisy speech recognition is proposed. Instead of assuming some statistical approximations as in the conventional model-based methods such as the PMC, the statistics necessary for the HMM parameter adaptation is directly estimated by using the Baum-Welch algorithm. The proposed method has shown improved results compared with the PMC for the noisy speech recognition.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.1
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• pp.158-164
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• 2002

This paper proposes the optimization of ultrasonic signal recognition in ferrite carbon steel weld zone using neural networks. For these purposes, the ultrasonic signals for defects as porosity, incomplete penetration and slag inclusion in the weld zone are acquired in the type of time series data. And then their applications evaluated feature extraction based on the time-frequency-attractor domain(peak to peak, rise time, rise slope, fall time, fall slope, pulse duration, power spectrum, and bandwidth) and attractor characteristics (fractal dimension and attractor quadrant) etc. The proposed neural networks system in this study can enhances performance of ultrasonic signal recognition.