• The Journal of the Acoustical Society of Korea
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• v.18 no.1E
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• pp.27-31
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• 1999

Recent linguistic researches have brought into focus the relations between prosodic structures and syntactic, semantic or phonological structures. Most of them prove that prosodic information is available for understanding syntactic, semantic and discourse structures. But this result has not been integrated yet into recent Korean speech recognition or understanding systems. This study, as a part of integrating prosodic information into the speech recognition system, proposes an automatic detection technique of Korean accentual phrase boundaries by using one-stage DP, and the normalized pitch pattern. For making the normalized pitch pattern, this study proposes a method of modified normalization for Korean spoken language. For the experiment, this study employs 192 sentential speech data of 12 men's voice spoken in standard Korean, in which 720 accentual phrases are included, and 74.4% of the accentual phrase boundaries are correctly detected while 14.7% are the false detection rate.

• Journal of Mechanical Science and Technology
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• v.14 no.5
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• pp.518-529
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• 2000

A detailed and thorough parametric study of digital image correlation method is presented. A theoretical background and development of the method were introduced and the effects of various parameters on the determination of displacement outputs from the raw original and deformed image information were examined. Use of the normalized correlation coefficient, the use of 20 to 40 pixels for a searching window side, 6 variables searching, bi-cubic spline sub pixel interpolations and the use of coarse-fine search are some of the key choices among the results of parametric studies. The displacement outputs can be further processed with two dimensional curve fitting for the data noise reduction as well as displacement gradient calculation.

• Journal of Mechanical Science and Technology
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• v.14 no.10
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• pp.1151-1158
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• 2000

Combustion analysis based on cylinder-pressure provides a mechanism through which a combustion researcher can understand the combustion process. The objective of this paper was to identify the most significant sources of cycle-to-cycle combustion variability in a spark ignition engine at idle. To analyse the cyclic variation in a test engine, the burn parameters are determined on a cycle-to-cycle basis through the analysis of the engine pressure data. The burn rate analysis program was used here and the burn parameters were used to determine the variations in the input parameter-i. e., fuel, air, and residual mass. In this study, we investigated the relationship of indicated mean effective pressure (IMEP), coefficient of variation (COV) of IMEP, burn angles, and lowest normalized value (LNV) in a spark ignition engine in a view of cyclic variations.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.31-36
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• 1998

By using wind vectors observed by NSCAT and significant wave heights observed by TOPEX/POSEIDON and ERS-2 altimeters, one-dimensional fetch growth of wind waves Is investigated under conditions of strong wind and high waves of the East Asian winter monsoon. The evolution of fetch-limited wind waves can be observed by the altimeters along the ground tracks. The fetch is estimated by using vector wind field observed by NSCAT. The derived growth characteristics of wind waves are compared with empirical relationships between the non-dimensional fetch and significant wave height proposed by previous studies. Good agreement with the empirical fetch graph formula normalized by the friction velocity is discemible, while the formulas normalized by the wind speed at a height of 10 m tend to underestimate the wave height under such severe conditions of high wind and very long fetch.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.2
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• pp.61-68
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• 2012

This paper describes a normalized numeric image descriptor used to assess the luminance and contrast of the image. The proposed image descriptor used the each pixel data as weighted value of the probability density function (PDF) and defined by normalization in order to objective represent. The proposed image numeric descriptor can be used to the adaptive gamma process because it suggests the objective basis of the gamma value selection.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.7A
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• pp.978-985
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• 2000

Blind equalizers recover the transmitted data using statistical characteristics of the signal alone. Among many alternatives, steepest gradient descent type algorithms such as the CMA and Sato algorithm are most widely utilized in practice. In this paper we propose a dual-mode NCMA algorithm, which combines the advantages of the dual mode CMA and Normalized CMA (NCMA) with the dual mode phase recovery algorithm. In addition, we perform computer simulations to demonstrate the performance improvement of the proposed algorithm with a QAM system. Simulation results show that the presented algorithm has a faster convergence speed and smaller steady-state residual error than the CMA and dual-mode CMA.

• Smart Structures and Systems
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• v.25 no.6
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• pp.669-678
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• 2020

This paper focuses on the free vibration analysis of axially functionally graded (FG) Euler-Bernoulli beams. The material properties of the beams are assumed to obey the linear law distribution. The complexities in solving differential equation of transverse vibration of composite beams which limit the analytical solution to some special cases are overcome using the Differential Transformation Method (DTM). Natural frequencies and corresponding normalized mode shapes are calculated. Validation targets are experimental data or finite element results. Different parameters such as reinforcement distribution, ratio of the reinforcement Young's modulus to the matrix Young's modulus and ratio of the reinforcement density to the matrix density are taken into investigation. The delivered results prove the capability and the robustness of the applied method. The studied parameters are demonstrated to be very crucial for the normalized natural frequencies and mode shapes.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.8
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• pp.640-646
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• 2003

We presents an edge-based point correlation algorithm for fast and stable visual inspection system. Conventional algorithms based on NGC(normalized gray-level correlation) have to overcome some difficulties in applying automated inspection systems to real factory environment. First of all, NGC algorithms involve highly complex computation and thus require high performance hardware for realtime process. In addition, lighting condition in realistic factory environments is not stable and therefore intensity variation from uncontrolled lights gives many troubles for applying NGC directly as pattern matching algorithm. We propose an algorithm to solve these problems, using thinned and binarized edge data, which are obtained from the original image. A point correlation algorithm with the thinned edges is introduced with image pyramid technique to reduce the computational complexity. Matching edges instead of using original gray-level image pixels overcomes problems in NGC method and pyramid of edges also provides fast and stable processing. All proposed methods are proved by the experiments using real images.

• Proceedings of the IEEK Conference
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• 2001.06e
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• pp.77-80
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• 2001

In this paper, we devised volume pulse detection system which can quantitatively represent a artery elasticity for oriental clinic. Volume pulse wave detecter system consist of transducer which has IRLED-photodiode detecter, temperature sensor and filter and preprocessing circuits, data conversion and serial communication parts, and computer system. The high-pass filter are detect volume pulse wave and lowpass filter detect tissue thickness. The detected volume pulse wave are normalized by tissue thickness value with a division process. As the result of experiment, we can detect normalized volume pulse wave with effectively.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.1
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• pp.68-75
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• 1999

Machine recognition of faces from still and video images is emerging as an active research area spanning several disciplines such as image processing, pattern recognition, computer vision and neural networks. In addition, human face identification has numerous applications such as human interface based systems and real-time video systems of surveillance and security. In this paper, we propose an algorithm that can identify a particular individual face. We consider human face identification system in color space, which hasn't often considered in conventional in conventional methods. In order to make the algorithm insensitive to luminance, we convert the conventional RGB coordinates into normalized CIE coordinates. The normalized-CIE-based facial images are KL-transformed. The transformed data are used as the input of multi-layered neural network and the network are trained using error-backpropagation methods. Finally, we verify the system performance of the proposed algorithm by experiments.