• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.1019-1032
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• 2013

The accurate prediction of future mortality is an important issue due to recent rapid increases in life expectancy. An accurate estimation and prediction of mortality is important to future welfare policies. The optimal selection of a mortality model is important to estimate and predict mortality; however, the period of time series data used is also an important issue. It is essential to understand that the time series data for mortality is short in Korea and the data before 1982 is incomplete. This paper divides the time series of Korean mortality into two sets to compare the parameter estimates of the LC model and LC model with a cohort effect by the period of data used. A modeling and prediction of the mortality index and cohort effect index as well as the evaluation of future life expectancy is conducted. Finally, some suggestions are proposed for the future prediction of mortality.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.31 no.7
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• pp.450-454
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• 2018

Because of the rapidly changing environment and high uncertainties, the semiconductor industry is in need of appropriate forecasting technology. In particular, both the cost and time in the test process are increasing because the process becomes complicated and there are more factors to consider. In this paper, we propose a prediction model that predicts a final "good" or "bad" on the basis of preconditioning test data generated in the semiconductor test process. The proposed prediction model solves the classification and regression problems that are often dealt with in the semiconductor process and constructs a reliable prediction model. We also implemented a prediction model through various machine learning algorithms. We compared the performance of the prediction models constructed through each algorithm. Actual data of the semiconductor test process was used for accurate prediction model construction and effective test verification.

• Bioinformatics and Biosystems
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• v.1 no.1
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• pp.82-87
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• 2006

The most popular protein structure prediction method is comparative modeling. To guarantee accurate comparative modeling, the sequence alignment between a query protein and a template should be accurate. Although choosing the best template based on the protein sequence alignments is most critical to perform more accurate fold-recognition in comparative modeling, even more critical is the sequence alignment quality. Contrast to a lot of attention to developing a method for choosing the best template, prediction of alignment accuracy has not gained much interest. Here, we develop a method for prediction of the shift score, a recently proposed measure for alignment quality. We apply support vector regression (SVR) to predict shift score. The alignment between a query protein and a template protein of length n in our own library is transformed into an input vector of length n +2. Structural alignments are assumed to be the best alignment, and SVR is trained to predict the shift score between structural alignment and profile-profile alignment of a query protein to a template protein. The performance is assessed by Pearson correlation coefficient. The trained SVR predicts shift score with the correlation between observed and predicted shift score of 0.80.

• Structural Engineering and Mechanics
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• v.54 no.3
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• pp.501-520
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• 2015

Presence of torsional loadings can significantly affect the flow of internal forces and deformation capacity of reinforced concrete (RC) columns. It increases the possibility of brittle shear failure leading to catastrophic collapse of structural members. This necessitates accurate prediction of the torsional behaviour of RC members for their safe design. However, a review of previously published studies indicates that the torsional behaviour of RC members has not been studied in as much depth as the behaviour under flexure and shear in spite of its frequent occurrence in bridge columns. Very few analytical models are available to predict the response of RC members under torsional loads. Softened truss model (STM) developed in the University of Houston is one of them, which is widely used for this purpose. The present study shows that STM prediction is not sufficiently accurate particularly in the post cracking region when compared to test results. An improved analytical model for RC square columns subjected to torsion with and without axial compression is developed. Since concrete is weak in tension, its contribution to torsional capacity of RC members was neglected in the original STM. The present investigation revealed that, disregard to tensile strength of concrete is the main reason behind the discrepancies in the STM predictions. The existing STM is extended in this paper to include the effect of tension stiffening for better prediction of behaviour of square RC columns under torsion. Three different tension stiffening models comprising a linear, a quadratic and an exponential relationship have been considered in this study. The predictions of these models are validated through comparison with test data on local and global behaviour. It was observed that tension stiffening has significant influence on torsional behaviour of square RC members. The exponential and parabolic tension stiffening models were found to yield the most accurate predictions.

• Tribology and Lubricants
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• v.18 no.2
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• pp.160-166
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• 2002

In case of rough contact fatigue, the accurate calculation of surface tractions is essential to the prediction of crack initiation life. Accurate Surface tractions influencing shear stress amplitude can be obtained by contact analysis based on the morphology of contact surfaces. In this study, to simulate rough contact under sliding condition, gaussian rough surface generated numerically in the previous study was used and to calculate clack initiation life in the substrate, dislocation pileup theory was used.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2000.11a
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• pp.72-79
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• 2000

In case of rough contact fatigue, the accurate calculation of surface tractions is essential to the prediction of crack initiation life. Accurate Surface tractions influencing shear stress amplitude can be obtained by contact analysis based on tile morphology of contact surfaces. In this study, to simulate rough contact under sliding condition, gaussian rough surface generated numerically in the previous study was used and to calculate crack initiation life in the substrate, dislocation pileup theory was used.

• Journal of KSNVE
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• v.7 no.6
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• pp.1001-1006
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• 1997

Railroad noise is one of the main causes of environmental impact. Whenever a new railroad line is planned or a housing project near an existing railroad is proposed, an estimate of the relevant noise levels is usually required. For this, it is necessary to quantify those paramters that affect the railroad noise. This paper presents an accurate prediction of railroad noise.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1994.10a
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• pp.92-95
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• 1994

Railroad noise is one of the main causes of environmental impact. Whenever a new railroad line is planned or a housing project near an existing railroad is proposed, an estimate of the relevant levels is usually required. For this, it is necessary to quantify those parameters that affect the railroad noise. This paper presents an accurate prediction of railroad noise.

• Journal of Biomedical Engineering Research
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• v.14 no.1
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• pp.1-8
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• 1993

In this study, the extractions of formants and articulatory motion trajectories for Korean complex vowels are performed by using the RLSL adaptive linear prediction filter. This enables us to extract accurate spectrum in transition of speech signal. This study shows that the RLSL algorithm is superior to the Levinson algorithm, specially in transition part of speech.

• Journal of information and communication convergence engineering
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• v.1 no.4
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• pp.189-193
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• 2003

A new algorithm is presented for adaptive notch filtering of narrow band or sine signals for embedded among broad band noise. The notch filter is implemented as a constrained infinite impulse response filter with a minimal number of parameters, Based on the recursive prediction error (RPE) method, the algorithm has the advantages of the fast convergence, accurate results and initial estimate of filter coefficient and its covariance is revealed. A convergence criterion is also developed. By using the information of the noise-to-signal power, the algorithm can self-adjust its initial filter coefficient estimate and its covariance to ensure convergence.