• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.240-240
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• 2000

This paper presents two algorithms based on the concept of the frequency domain adaptive filter(FDAF). First the frequency domain recursive least squares(FRLS) algorithm with the overlap-save filtering technique is introduced. This minimizes the sum of exponentially weighted square errors in the frequency domain. To eliminate discrepancies between the linear convolution and the circular convolution, the overlap-save method is utilized. Second, the sliding method of data blocks is studied Co overcome processing delays and complexity roads of the FRLS algorithm. The size of the extended data block is twice as long as the filter tap length. It is possible to slide the data block variously by the adjustable hopping index. By selecting the hopping index appropriately, we can take a trade-off between the convergence rate and the computational complexity. When the input signal is highly correlated and the length of the target FIR filter is huge, the FRLS algorithm based on the block processing technique has good performances in the convergence rate and the computational complexity.

• 한국지구물리탐사학회:학술대회논문집
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• 2007.06a
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• pp.81-86
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• 2007

Spectral features of the seismic wave propagation from Odaesan Earthquake were evaluated based on the commonly treated random error between the observed data and the prediction values by the stochastic point-source ground-motion spectral model regarding the source, path and site effects. Radiation pattern of the error according to azimuth angle was found to be similar to the theoretical estimate. It was also observed that the spatial distribution of the errors was correlated with the geological map and the Q0 map which are indicatives of seismic boundaries.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.23 no.6
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• pp.627-633
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• 2010

This paper presents a method for identifying the parameter set of inelastic constitutive equations, which is based on an Evolutionary Algorithm. The advantage of the method is that appropriate parameters can be identified even when the measured data are subject to considerable errors and the model equations are inaccurate. The design of experiments suited for the parameter identification of a material model by Chaboche under the uniaxial loading and stationary temperature conditions was first considered. Then the parameter set of the model was identified by the proposed method from a set of experimental data. In comparison to those by other methods, the resultant stress-strain curves by the proposed method correlated better to the actual material behaviors.

• Phonetics and Speech Sciences
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• v.3 no.1
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• pp.15-22
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• 2011

The purposes of this study are (1) to investigate the correlation between English word-final stop and the duration of vowels before word-final stop and (2) to suggest a way to detect pronunciation errors and teach the pronunciation of English word-final stops. For these purposes, 18 Korean speakers' production was recorded and analysed using Speech Analyzer and their production was compared with that of native English speakers. In addition, two native English speakers evaluated the subjects' pronunciation. The major findings are the voicing dependent effect of the English vowels produced by native Korean speakers is lower than that of native English speakers; Korean speakers release English word-final stops less than native English speakers; and the pronunciation of English word-final stops and the duration of adjacent vowels are closely related in that the pronunciation score of final stops and the ratio of vowels between the vowels before voiced stops and voiceless stops are correlated. In addition, this study concludes with pedagogical suggestions that may be useful for English pronunciation teaching.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.4
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• pp.57-65
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• 2011

Monitoring auto correlated processes is prevalent in recent manufacturing environments. As a proactive control for manufacturing processes is emphasized especially in the semiconductor industry, it is natural to monitor real-time status of equipment through sensor rather than resultant output status of the processes. Equipment's sensor data show various forms of correlation features. Among them, considerable amount of sensor data, statistically autocorrelated, is well represented by Box-Jenkins autoregressive moving average (ARMA) model. In this paper, we present a design method of statistical process control (SPC) used for monitoring processes represented by the ARMA model. The proposed method shows benefits in the power of detecting process changes, and considers robustness to ARMA modeling errors simultaneously. We prove benefits through Monte carlo simulation-based investigations.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.11a
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• pp.262-265
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• 2001

In order to investigate the water tree degradation behavior on XLPE cable, direct voltage of 200 to 800V has been applied to the material at 50$^{\circ}C$∼100$^{\circ}C$, and the water tree property has been correlated with voltage and temperature in this study. The leakage current was shown to increase as temperature increased and the Ohm's law was generally satisfied in this experiment though some experimental errors were found. The leakage current was shown to decrease and reach to the stable state with time. It was also shown that the time for the stabilization of leakage current was lessened as voltage increased

• East Asian Economic Review
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• v.25 no.4
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• pp.403-424
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• 2021

AdaBoost tweaks the sample weight for each training set used in the iterative process, however, it is demonstrated that it provides more correlated errors as the boosting iteration proceeds if models' accuracy is high enough. Therefore, in this study, we propose a novel way to improve the performance of the existing AdaBoost algorithm by employing heterogeneous models and a stochastic twist. By employing the heterogeneous ensemble, it ensures different models that have a different initial assumption about the data are used to improve on diversity. Also, by using a stochastic algorithm with a decaying convergence rate, the model is designed to balance out the trade-off between model prediction performance and model convergence. The result showed that the stochastic algorithm with decaying convergence rate's did have a improving effect and outperformed other existing boosting techniques.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.11
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• pp.1084-1093
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• 2012

For large multihop networks, large time synchronization (TS) errors can accumulate with conventional methods, such as TPSN, RBS, and FTSP, since they need a large number of hops to cover the network. In this paper, a method combining Concurrent Cooperative Transmission (CCT) and Semi- Cooperative Spectrum Fusion (SCSF) is proposed to reduce the number of hops to cover the large network. In CCT, cooperating nodes transmit the same digitally encoded message in orthogonal channels simultaneously, so receivers can benefit from array and diversity gains. SCSF is an analog cooperative transmission method where different cooperators transmit correlated information simultaneously. The two methods are combined to create a new distributed method of network TS, called the Cooperative Analog and Digital (CANDI) TS protocol, which promises significantly lower network TS errors in multi-hop networks. CANDI and TPSN are compared in simulation for a line network.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.03a
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• pp.493-498
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• 2004

The objective of the present study is to compare various conventional and recently evolved satellite image-processing techniques and to ascertain the best possible technique that can identify and position of aquaculture farms accurately in and around the Younggwang coastal area. Several conventional techniques performed to extract such information fiom the Landsat-TM imagery do not seem to yield better information about the aquaculture farms, and lead to misclassification. The large errors between the actual and extracted aquaculture farm information are due to existence of spectral confusion and inadequate spatial resolution of the sensor. This leads to possible occurrence of mixture pixels or 'mixels' of the source of errors in the classification techniques. Understanding the confusing and mixture pixel problems requires the development of efficient methods that can enable more reliable extraction of aquaculture farm information. Thus, the more recently evolved methods such as the step-by-step partial spectral end-member extraction and linear spectral unmixing methods are introduced. The farmer one assumes that an end-member, which is often referred to as 'spectrally pure signature' of a target feature, does not appear to be a spectrally pure form, but always mix with the other features at certain proportions. The assumption of the linear spectral unmxing is that the measured reflectance of a pixel is the linear sum of the reflectance of the mixture components that make up that pixel. The classification accuracy of the step-by-step partial end-member extraction improved significantly compared to that obtained from the traditional supervised classifiers. However, this method did not distinguish the aquaculture ponds and non-aquaculture ponds within the region of the aquaculture farming areas. In contrast, the linear spectral unmixing model produced a set of fraction images for the aquaculture, water and soil. Of these, the aquaculture fraction yields good estimates about the proportion of the aquaculture farm in each pixel. The acquired proportion was compared with the values of NDVI and both are positively correlated (R$^2$ =0.91), indicating the reliability of the sub-pixel classification.ixel classification.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.26 no.3
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• pp.183-189
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• 2015

Objectives : The aim of this study was to investigate Korean Wechsler Intelligence profiles and specific abilities related to attention problem of children with attention-deficit hyperactivity disorder (ADHD). Methods : The Korean Wechsler Intelligence Scale for Children-fourth edition (K-WISC-IV) and Advanced Test of Attention (ATA) were administered to 91 children and adolescents (age $8.5{\pm}2.6$ years, 73 boys) with ADHD. Pearson correlation and independent t-tests were used. Results : The means of Working Memory Index (WMI) and Processing Speed Index (PSI) showed a score of low average in K-WISC-IV. WMI scores for the K-WISC-IV showed clinically significant correlations with omission errors, commission errors, and response time variability on auditory ATA. PSI scores also showed significant correlations with response time and variability on visual ATA. In addition, significantly lower digit span backward scores were observed in hyperactive-impulsive/combined subtypes compared to inattentive subtype (t=3.60, p<.001). Conclusion : Children with ADHD showed significantly lower scores in WMI and PSI which were clinically correlated with ATA scores, and hyperactive-impulsive/combined subtypes showed poorer working memory functions in WMI. Follow-up studies are proposed.