• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.3 no.4
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• pp.23-27
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• 2010

This paper performs emotion classification test to find out the best parameter of electroencyphalogram(EEG) signal. Linear predictor coefficients, band cross-correlation coefficients of fast Fourier transform(FFT) and autoregressive model spectra are used as the parameters of 10-channel EEG signal. A multi-layer neural network is used as the pattern classifier. Four emotions for relaxation, joy, sadness, irritation are induced by four university students of an acting circle. Electrode positions are Fp1, Fp2, F3, F4, T3, T4, P3, P4, O1, O2. As a result, the Linear predictor coefficients showed the best performance.

• Journal of applied mathematics & informatics
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• v.9 no.2
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• pp.807-815
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• 2002

We consider a more general linear regression super-population model than the one of Chaudhuri and Stronger(1992) . We can find the same type of the best linear unbiased(BLU) predictor as that of Chaudhuri and Stenger and see that the optimal design is again a purposive one which prescribes choosing one of the samples of size n which has $\chi$ closest to $\bar{X}$.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.260-263
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• 2000

A technique that uses linear prediction to achieve noise reduction in a voice signal which has been mixed with an ambient noise (Signal to Noise (S-N) ratio = about 0dB) is proposed. This noise reduction method which is based on the linear prediction estimates the voice spectrum while ignoring the spectrum of the noise. The performance of the noise reduction method is first examined using the transversal linear predictor filter. However, with this method there is deterioration in the tone quality of the predicted voice due to the low level of the S-N ratio. An additional processing circuit is then proposed so as to adjust the noise reduction circuit with an aim of improving the problem of tone deterioration. Next, we consider a practical application where the effects of round on errors arising from fixed-point computation has to be minimized. This minimization is achieved by using the lattice predictor filter which in comparison to the transversal type, is Down to be less sensitive to the round-off error associated with finite word length operations. Finally, we consider a practical application where noise reduction is necessary. In this noise reduction method, both the voice spectrum and the actual noise spectrum are estimated. Noise reduction is achieved by using the linear predictor filter which includes the control of the predictor filter coefficient’s update.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.12 no.1
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• pp.9-18
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• 1987

An electro-optic system using linear photosensitive Charge Coupled Devices(CCDs) having dummy pixels has been proposed for realzation of linear prodictor in the differential pulse code modulation(DPCM). The system consists of three components as conventional system:input light source, spatial filter(mask) and CCD line scanning sensor. For the delay time due to the dummy pixels in CCD, modifying conventional mask, a new dispersive mask is proposed, of which every prediction coefficient is dispersed on the more than one element, the characteristics of the system using the proposed dispersive mask are analyzed theoretically and verified with experiment.

• Communications for Statistical Applications and Methods
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• v.20 no.2
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• pp.147-155
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• 2013

To determine whether each coefficient is equal to zero or not, usual $t$-tests are a popular choice (among others) in linear regression to practitioners because all statistical packages provide the statistics and their corresponding $p$-values. Under smaller samples (especially with non-normal errors) the tests often fail to correctly detect statistical significance. We propose a permutation approach by adopting a sufficient dimension reduction methodology to overcome this deficit. Numerical studies confirm that the proposed method has potential advantages over the t-tests. In addition, data analysis is also presented.

• Journal of the Korean Institute of Telematics and Electronics
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• v.19 no.4
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• pp.1-5
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• 1982

A new algorithm, based upon a lattice formulation, is presented for linear prediction. The output of the algorithm is the reflection coefficients that guarantee the stability of the all-pole model. The equations are derived that compute the covariance of the residuals recursively at each prediction stage, and in processing of computing that eqations, the reflection coefficients are estimated without computing the predictor coefficients. Comparing with covariance-lattice method, it can be said that the new algorithm reduce the number of computations to about half and is more efficient for fitting of the high-order model.

• Journal of Biosystems Engineering
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• v.34 no.6
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• pp.434-438
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• 2009

This study was conducted to design an cone penetrometer type impedance sensor that can measure soil water content in realtime. The best width between electrical probe was determined by 5 mm. For optimization about realtime application device, linear regression analysis was applied between soil water content and impedance signal. It was concluded that proper combination of excitation frequency, impedance parameter, and model would provide acceptible performance of a soil waler content sensoe. Best model was obatained at a 36.5 MHz with |Z| as a predictor variable, with a coefficient of determination of 0.96 (RMSE=1.35, RPD=4.98).

• Journal of Forest and Environmental Science
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• v.28 no.2
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• pp.63-67
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• 2012

Crown ratio is the ratio of live crown length to tree height. It is often used as an important predictor variable for tree growth equation. It indicates tree vigor and is a useful parameter in forest health assessment. The objective of the study was to develop crown ratio prediction models for Tectona grandis. Based on the data set from the temporary sample plots, several non linear equations including logistics, Chapman Richard and exponential functions were tested. These functions were evaluated in terms of coefficient of determination ($R^2$) and standard error of the estimate (SEE). The significance of the estimated parameters was also verified. Plot of residuals against estimated crown ratios were observed. Although the logistic model had the highest $R^2$ and the least SEE, Chapman-Richard and Exponential functions were observed to be more consistent in their predictive ability; and were therefore recommended for predicting crown ratio in the stand.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.33-36
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• 1988

In this paper, the starting point of affricate is detected from the first predictor coefficient of a 12-pole linear predictive coding (LPC) analysis and phonemic segmentation is done through measuring short time energy and zero crossing rate. By this segmentation method, the duration of an aspirate can be mearsured in order to detect an aspirate or not.

• Research in Community and Public Health Nursing
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• v.14 no.4
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• pp.686-698
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• 2003

Purpose: This is a descriptive correlation study purposed to provide basic data for comprehensive nursing care by analyzing the relationship between the burden and the quality of life of family caregivers of cancer patients treated with chemotherapy. Methods: As for the subjects of this study, 66 family caregivers who take care of cancer patients hospitalized and treated with chemotherapy participated in the research. The tool of this study was a structured questionnaire including questions concerning burden(19 items) and the quality of life(33 items). Collected data were analyzed using SPSS PC+ program through descriptive statistics, t-test, ANOVA, Pearson's correlation coefficient, and stepwise multiple linear regression. Results: 1) The mean score of burden was 2.6383. The mean score of quality of life was 3.3034. These score show that family caregivers perceive a moderate level of burden and the quality of life. 2) Family caregivers' burden was significantly related to symptoms in the cancer patient (r= 0.3501, P=0.0042) and family caregivers(r= 0.5340, P=0.0001). Family caregivers' quality of life was significantly related to symptoms in the cancer patient(r= -0.3528, P=0.0039) and family caregivers(r= -0.5472, P=0.0001). According to the result of examining' the relationship between burden and the quality of life, there was a statistically negative correlation(r= -0.6326, P=0.0001). 3) 'Family income after the onset of the patient' was the most important predictor of the burden of family caregivers($R^2$=0.158). 'Usual relationship with the patient' was the most important predictor of the quality of life of family caregivers($R^2$=0.138). Conclusions: The results presented above indicate that we must consider burden of family caregivers and symptoms experienced by them in order to improve the quality of life of family caregivers of cancer patients treated with chemotherapy.