• Archives of Pharmacal Research
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• v.11 no.1
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• pp.45-51
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• 1988

The feature of resolution enhancement by derivative operation is linked to one of the multivariate analysis, which is multiple linear regression with two options, all possible and stepwise regression. Examined samples were synthetic mixtures of 5 vitamins, thiamine mononitrate, riboflavin phosphate, nicotinamide, pyridoxine hydrochloride and ascorbic acid. All components in mixture were quantified with reasonably good accuracy and precision. Whole data processing procedure was accomplished on-line by the development of three computer programs written in APPLESOFT BASIC language.

• Restorative Dentistry and Endodontics
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• v.44 no.1
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• pp.11.1-11.8
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• 2019

In the previous sections, simple linear regression (SLR) 1 and 2, we developed a SLR model and evaluated its predictability. To obtain the best fitted line the intercept and slope were calculated by using the least square method. Predictability of the model was assessed by the proportion of the explained variability among the total variation of the response variable. In this session, we will discuss four basic assumptions of regression models for justification of the estimated regression model and residual analysis to check them.

• The Research Journal of the Costume Culture
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• v.5 no.4
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• pp.130-158
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• 1997

This study outputs calculation of regression of each items for production of torso basic pattern according to 6 body types as the result of another study and intends to present drawing method of torso model by short measure method modified and supplied and supplied by experiments of wearing clothing. SAS(Statistical Analysis System) is used for figures management and methods for analysis used are Frequency Analysis, Means Analysis, Regression Analysis, Correlation Analysis, etc. Results are as follows. 1. Correlation analysis is used to output the size necessary for torso prototype drawing by sort measure method and waist front length, back length, crotch length, shoulder point-cerricale-shoulder point, bust circumference, waist circumference, weight, etc, are set up as representative items calculation of regression of each type is suggested. 2. In the result of experiment of the first wearing clothing intended for 5 in each type and the whole 30, to develop torso prototype drawing method by short measure method, as we find some problems of the shape and propriety of neck root circumference line, the position of shoulder point, pulling or hold armpit parts, waist circumference line, the degree of dissatisfaction is high, so the second experiment of wearing clothing is propriety of each part is improved, all items except the length and quantity of shoulder dart, waist in back bodice, clearance quantity of hip circumference, and the place of shoulder line in side bodice. So, it was modifed and supplied and then the third torso prototyped drawing method by shout measure method was suggested. The third prototype drawing method was suggested, by modifying and supplying.

• Journal of Sericultural and Entomological Science
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• v.39 no.2
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• pp.174-179
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• 1997

The larval head capsule width, larval weight and length of mulberry longicorn beetle, Apriona germari Hope were measured when the larvae were exuviated in artificial diet rearing. The larval head capsule width from the 1st to the 12th instar was ranged from 0.12 to 0.69 cm, and growth ratio of each instar was significantly high between the 1st and the 2nd instars. The fitness to Dyar's law for the larval head capsule width was 87.6%. When the logarithum of the larval head capsule width is plotted against the number of instars, the calculated regression line was LogY=0.12086+0.06998X and Dyar's constant was 1.18. The larval weight was increased with larval developmental stages, and the coefficient of variation of larval weight was apparently high. But the calculated regression line was LogY=-0.91592+0.25959X and Dyar's constant was 1.25. The growth ration of the larval length was clearly high between the 2nd and the 3rd instars, and that of larvae from the 4th instar was decreased. The calculated regression line was LogY=-0.16932+0.09841X and Dyar's constant was 1.25. In conclusion, our results suggested that the larvae growth of mulberry longicorn beetle appeared to be highly related in the larval head capsule width, larval weight and length.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.3
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• pp.527-535
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• 2008

Many signal processing techniques have been described in the literature for estimating amplitude, frequency and duration variables of the surface EMG signal detected during constant voluntary contractions. They have been used in different application areas for the non-invasive assessment of muscle function. The main purpose of our research is to compare the most frequently used algorithms for information extraction from surface EMG signals under varying conditions in terms of the different window lengths, muscle contraction levels, muscles and subjects. In particular we focus on the issue of estimating the slope and intercept to resolve an linear regression line with utilizing real SEMG signals which represents voluntary contractions during thirty seconds.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1249-1253
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• 2005

This paper presents a method to model the path loss characteristics in microwave urban line-of-sight (LOS) propagation. We propose new upper- and lower-bound models for the LOS path loss using fuzzy linear regression (FLR). The spread of upper- and lower-bound of FLR depends on max and min value of a sample path loss data while the conventional upper- and lower-bound models, the spread of the bound intervals are fixed and do not depend on the sample path loss data. Comparison of our models to conventional upper- and lower-bound models indicate that improvements in accuracy over the conventional models are achieved.

• Asian-Australasian Journal of Animal Sciences
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• v.15 no.5
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• pp.622-626
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• 2002

Growth records over six generations of 686 pigs in SD-II Swine Line were used to estimate the genetic and phenotypic covariance functions for body weight as longitudinal data. A random regression model with Legendre polynomials of age as independent variables was used to estimate the (co)variances among the regression coefficients, thus the coefficients of genetic and permanent environmental covariance functions by restricted maximum likelihood employing the average information algorithm. The results showed that, using litter effect as additional random effect, a reduced order of fit did not describe the data adequately. For all five orders of fit, however, the change trends of genetic and phenotypic (co)variances were very similar from ${\kappa}$=3 onwards.

• Proceedings of the KIPE Conference
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• 2006.06a
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• pp.345-347
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• 2006

In this paper, a novel method for wind speed estimation in wind power generation systems is presented. The proposed algorithm is based on estimating the wind speed using Support-Vector-Machines for regression (SVR). The wind speed is estimated using the generator power-speed characteristics as a set of training vectors. SVR is trained off-line to predict a continuos-valued function between the system's inputs and wind speed value. The predicted off-line function as well as the instantaneous generator power and speed are then used to determine the unknown winds speed on-line. The simulation results show that SVR can define the corresponding wind speed rapidly and accurately to determine the optimum generator speed reference for maximum power point tracking.

• The Korean Journal of Applied Statistics
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• v.24 no.5
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• pp.759-768
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• 2011

Tree algorithms have been widely developed for regression problems. One of the good features of a regression tree is the flexibility of fitting because it can correctly capture the nonlinearity of data well. Especially, data with sudden structural breaks such as the price of oil and exchange rates could be fitted well with a simple mixture of a few piecewise linear regression models. Now that split points are determined by chi-squared statistics related with residuals from fitting piecewise linear models and the split variable is chosen by an objective criterion, we can get a quite reasonable fitting result which goes in line with the visual interpretation of data. The piecewise linear regression by a regression tree can be used as a good fitting method, and can be applied to a dataset with much fluctuation.

• International Journal of Human Ecology
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• v.13 no.1
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• pp.105-115
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• 2012

This research investigated the influences of structural characteristics such as fabrics, mechanical properties, and subjective sensory images on the off-line and on-line preferences to women's spring/summer suits fabrics to extract the most effective factor towards preference as well as analyze the preferential off-line and on-line differences to predict the exact texture image on-line. Objective evaluations were done for the measurement of the mechanical properties of fabrics using Kawabata's Evaluation System and subjective evaluations were done with 109 female subjects who value the off-line and on-line sensory image of suit fabrics. For statistical analysis, factor analysis, cluster analysis, t-test, ANOVA, and regression were used. The results were as follows. The preference scores on-line were generally higher than those off-line. For the structural characteristics of fabrics, differences of thickness were observed according to preference clusters, and the preference increased as thickness was lowered off-line and on-line. For mechanical properties, WC influenced off-line and on-line preferences. Fabrics with low compression energy were preferred; however, the effect of SMD was observed off-line only. In subjective sensory images, the 'smoothness' image influenced off-line and on-line preferences the most. All sensory images influenced the off-line preferences; however, the effects of 'flexibility' and 'weight' were not shown on-line.