• The Journal of the Acoustical Society of Korea
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• v.14 no.1
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• pp.31-39
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• 1995

In this paper, we have constructed phoneme discriminant filters [PDF] according to the linear discriminant function. These discriminant filters do not follow the heuristic rules by the experts but the mathematical methods in iterative learning. Proposed system. is based on the piecewise linear classifier and error correction learning method. The segmentation of speech and the classification of phoneme are carried out simutaneously by the PDF. Because each of them operates independently, some speech intervals may have multiple outputs. Therefore, we introduce the unified coefficients by the output unification process. But sometimes the output has a region which shows no response, or insensitive. So we propose time windows and median filters to remove such problems. We have trained this system with the 549 monosyllables uttered 3 times by 3 male speakers. After we detect the endpoint of speech signal using threshold value and zero crossing rate, the vowels and consonants are separated by the PDF, and then selected phoneme passes through the following PDF. Finally this system unifies the outputs for competitive region or insensitive area using time window and median filter.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.1
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• pp.77-82
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• 2004

In this paper we present a barcode reader to decode two-dimensional symbology PDF417 and propose a novel method to extract the bar-space Patterns directly from the gray-level barcode image, which employs the location and the distance between extreme points of each row or column of the barcode image. This algerian proves to be very robust from the high convolutional distortion environments such as defocussing and warping, even under badly illuminating condition. If the scanned barcode image is a result of the convolution of a Gaussian-shaped point spread function with a hi-level image, popular image segmentation methods such as image thresholding can not distinguish between very narrow bar-space patterns. The Proposed algorithm shows improved Performance over current barcode readers.

• Journal of Korea Multimedia Society
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• v.12 no.8
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• pp.1155-1163
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• 2009

This paper proposes an automatic facial expression generation system of vector graphic character using gaussian process model. Proposed method extracts the main feature vectors from twenty-six facial data of character redefined based on Russell's internal emotion state. Also by using new gaussian process model, SGPLVM, we find low-dimensional feature data from extracted high-dimensional feature vectors, and learn probability distribution function (PDF). All parameters of PDF are estimated by maximization the likelihood of learned expression data, and these are used to select wanted facial expressions on two-dimensional space in real time. As a result of simulation, we confirm that proposed facial expression generation tool is working in the small facial expression datasets and can generate various facial expressions without prior knowledge about relation between facial expression and emotion.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.437-438
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• 2009

• International Journal of Aeronautical and Space Sciences
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• v.14 no.1
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• pp.85-90
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• 2013

This paper presents a study on terrain referenced navigation (TRN). The extended Kalman filter (EKF) is adopted as a filter method. A Jacobian matrix of measurement equations in the EKF consists of terrain slope terms, and accurate slope estimation is essential to keep filter stability. Two slope estimation methods are proposed in this study. Both methods are based on the least-squares approach. One is planar regression searching the best plane, in the least-squares sense, representing the terrain map over the region, determined by position error covariance. It is shown that the method could provide a more accurate solution than the previously developed linear regression approach, which uses lines rather than a plane in the least-squares measure. The other proposed method is weighted planar regression. Additional weights formed by Gaussian pdf are multiplied in the planar regression, to reflect the actual pdf of the position estimate of EKF. Monte Carlo simulations are conducted, to compare the performance between the previous and two proposed methods, by analyzing the filter properties of divergence probability and convergence speed. It is expected that one of the slope estimation methods could be implemented, after determining which of the filter properties is more significant at each mission.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.1
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• pp.51-57
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• 2005

In this paper, we propose an adaptive contrast control method for the flat real-time processing. The proposed method has employed probability density function(PDF) in order to control a sudden change in image-brightness. In addition, the proposed algerian obtains the maximum contrast without affecting the processed image. In order to reduce hardware complexity, we have utilized approximated CDF based on sampling values. Visual test and standard deviation of their histogram have been introduced to evaluate the resultant output images of at: proposed method and the original ones.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.1
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• pp.61-67
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• 2017

For a project network analysis, a fundamental problem is to estimate the distribution function of the project completion time. In this paper, we propose a method for evaluating moments(mean, variance, skewness, kurtosis) of the project completion time under the assumption that the durations of activities are independently and normally distributed. The proposed method utilizes the technique of discretization to replace the continuous probability density function(pdf) of activity duration with its discrete pdf and a random number generation. The proposed method is easy to use for large-sized project networks, and the computational results of the proposed method indicate that the accuracy is comparable to that of direct Monte Carlo simulation.

• Journal of the Korean Geotechnical Society
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• v.25 no.12
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• pp.37-45
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• 2009

Dredging and reclamation which have been conducted steadily for creation of new coastal area have the demerit of taking a long time. Hence, a lot of researches on acceleration of self-weight consolidation have been proceeding continuously. In this paper, 30 cases of laboratory self-weight consolidation tests were conducted to understand the application of PDF method, one of the self-weight consolidation acceleration methods, to domestic dredged soils. Acceleration effect of self-weight consolidation was confirmed through comparison and analysis of completion times and settlements of self-weight consolidation for none installed case and 4 kinds of common used PBD installed cases. As a result of the tests, installation of PBD before filling is effective for time reduction of self-weight consolidation.

• 한국연소학회:학술대회논문집
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• 2014.11a
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• pp.183-184
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• 2014

The multi-environment probability density function model has been applied to simulate the turbulent stratified premixed flames. The direct quadrature method of moments (DQMOM) has been adopted to solve the transport PDF equation due to its computational efficiency and robustness. Computations are made for the non-swirling turbulent stratified premixed flames including SWB1, SWB5 and SWB9. The numerical results obtained in this study are precisely compared with experimental data in terms of axial velocity, unconditional means and conditional means for scalar field including temperature and species mass fraction.

• International journal of advanced smart convergence
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• v.9 no.1
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• pp.193-201
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• 2020

The main objective of this study is to investigate the impact of additional modalities on the performance of emotion recognition using speech, facial expression and physiological measurements. In order to compare different approaches, we designed a feature-based recognition system as a benchmark which carries out linear supervised classification followed by the leave-one-out cross-validation. For the classification of four emotions, it turned out that bimodal fusion in our experiment improves recognition accuracy of unimodal approach, while the performance of trimodal fusion varies strongly depending on the individual. Furthermore, we experienced extremely high disparity between single class recognition rates, while we could not observe a best performing single modality in our experiment. Based on these observations, we developed a novel fusion method, called parametric decision fusion (PDF), which lies in building emotion-specific classifiers and exploits advantage of a parametrized decision process. By using the PDF scheme we achieved 16% improvement in accuracy of subject-dependent recognition and 10% for subject-independent recognition compared to the best unimodal results.