• Journal of Korean Society for Quality Management
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• v.23 no.1
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• pp.95-105
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• 1995

The error structure of nonlinearized technological growth models, such as, the Pearl curve, the Gompertz curve and the Wei bull growth curve, has zero mean and a constant variance over time. Transformed models, however, like the linearized Fisher-Pry model. the linearized Gompertz growth curve, and the linearized Weibull growth curve have increasing variance from t = 0 to the inflection point.

• Journal of Korean Society for Quality Management
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• v.32 no.4
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• pp.265-273
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• 2004

We got the growth distance curve by spline smoothing method with observed marketing data and the growth velocity curve by the derivation of the growth distance curve. Using this growth velocity curve, we defined the several characteristic points which describe the variation of marketing data. In this paper, to specify several patterns of marketing data, we suggested characteristic function by using these characteristic points. In addition, we applied characteristic function to the seventeen brands of electric home products data.

• Journal of Korean Society for Quality Management
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• v.25 no.1
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• pp.44-55
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• 1997

In order to determine procedures for a, pp.opriate model selection of technological growth curves, numerous time series that were representative of growth behavior were collected according to data characteristics. Three different growth curve models were fitted onto data sets in an attempt to determine which growth curve models achieved the best forecasts for types of growth data. The analysis of the results gives rise to an a, pp.oach for selecting a, pp.opriate growth curve models for a given set of data, prior to fitting the models, based on the characteristics of the goodness of fit test.

• Journal of Animal Science and Technology
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• v.57 no.5
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• pp.19.1-19.6
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• 2015

The objective of this study was to estimate variance components and genetic parameters for growth curve parameters in Guilan sheep. Studied traits were parameters of Brody growth model which included A (asymptotic mature weight), B (initial animal weight) and K (maturation rate). The data set and pedigree information used in this study were obtained from the Agricultural Organization of Guilan province (Rasht, Iran) and comprised 8647 growth curve records of lambs from birth to 240 days of age during 1994 to 2014. Marginal posterior distributions of parameters and variance components were estimated using TM program. The Gibbs sampler was run 300000 rounds and the first 60000 rounds were discarded as a burn-in period. Posterior mean estimates of direct heritabilities for A, B and K were 0.39, 0.23 and 0.039, respectively. Estimates of direct genetic correlation between growth curve parameters were 0.57, 0.03 and -0.01 between A-B, A-K and B-K, respectively. Estimates of direct genetic trends for A, B and K were positive and their corresponding values were $0.014{\pm}0.003$ (P < 0.001), $0.0012{\pm}0.0009$ (P > 0.05) and $0.000002{\pm}0.0001$ (P > 0.05), respectively. Residual correlations between growth curve parameters varied form -0.52 (between A-K) to 0.48 (between A-B). Also, phenotypic correlations between growth curve parameters varied form -0.49 (between A-K) to 0.47 (between A-B). The results of this study indicated that improvement of growth curve parameters of Guilan sheep seems feasible in selection programs. It is worthwhile to develop a selection strategy to obtain an appropriate shape of growth curve through changing genetically the parameters of growth model.

• Journal of the Korean Society for Precision Engineering
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• v.6 no.3
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• pp.78-89
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• 1989

Applicability of tearing modulus based on J-integral proposed by Paris et al is investigated using compact tension specimens of strutural alloy steel (SCM4). Both general fracture test and instability fracture test are performed. The applied tearing modulus, ( $T_{j}$)app estimated from the real load vs. crack growth curve measured from experiments are compared with that estimated from the limit load vs. crack growth curve. The results are : (1) the $T_{j}$parameter could be applied to predict crack growth instability : (2) The use of ( $T_{j}$)app estimated from the load vs. crack growth curve, proposed in this study could be well predicted crack growth instability instead of that estimated form the limit load vs. crack growth curve.e.

• 한국데이터정보과학회:학술대회논문집
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• 2001.10a
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• pp.67-75
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• 2001

A completely randomized growth curve model was defined by Zerbe(1979). We propose the fully significant difference procedure for multiple comparisons of completely randomized growth curve model. The standard F test is useful tool to multiple comparisons of the completely randomized growth curve model. The proposed method is applied to experimental data.

• Journal of the Korean Data and Information Science Society
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• v.14 no.2
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• pp.313-323
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• 2003

For the growth curve model with arbitrary covariance structure, known as unstructured covariance matrix, the problems of detecting outliers are discussed in this paper. In order to detect outliers in the growth curve model, the test statistics using U-distribution is established. After detecting outliers in growth curve model, we test homo and/or hetero-geneous covariance matrices using PSR Quasi-Bayes Criterion. For illustration, one numerical example is discussed, which compares between before and after outlier deleting.

• Journal of the Korean Ceramic Society
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• v.33 no.2
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• pp.203-213
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• 1996

In this study the subcritical crack growth behavior in an Al2O3-SiCw composite has been investigated using in situ fracture technique of applied moment double cantilever beam (AMDCB) specimens indside an SEM. This technique allows the detailed observation of whisker and grain bridging in the crack wake region. The experimental results indicated that the KI-a curve was deviated from the conventional powder law form and that the existed a region where the rate of microcrack growth was decreased with increasing the externally applied stress intensity factor. This behavior could be explained by arising crack growth resistance i.e. R-curve behavior which was associated with crack shielding due to whisker and grain bridging. The R-curve was also analyzed from the KI-a curve data in order to quantify the bridging effect in the Al2O3-SiCw composite.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.1
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• pp.76-86
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• 2020

Technology growth curve methodology is commonly used in technology forecasting. A technology growth curve represents the paths of product performance in relation to time or investment in R&D. It is a useful tool to compare the technological performances between Korea and advanced nations and to describe the inflection points, the limit of improvement of a technology and their technology innovation strategies, etc. However, the curve fitting to a set of survey data often leads to model mis-specification, biased parameter estimation and incorrect result since data through survey with experts frequently contain outlier in process of curve fitting due to the subjective response characteristics. This paper propose a method to eliminate of outlier from a technology growth curve using M-estimator. The experimental results prove the overall improvement in technology growth curves by several pilot tests using real-data in Defense Science and Technology Survey reports.

• The KIPS Transactions:PartD
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• v.11D no.3
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• pp.597-604
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• 2004

Accurate software cost estimation is essential to both developers and customers. Most of the cost estimating models based on the size measure methods, such as LOC and FP, are obtained through size estimation. The accuracy of size estimation directly influences the accuracy of cost estimation. As a result, the overall structure of regression-based cost models applies the power function based on software size. Many growth phenomenon in nature such as the growth in living organism, performance of technology, and learning capability of human show an S-shaped curve. This paper proposes a model which estimates the developing effort by using the growth curve. The presented model assumes that the relation cost and size follows the growth curve. The appropriateness of the growth curve model based on Function Point, Full-Function Point and Use-Case Point, which are the general methods in estimating the software size have been confirmed. The proposed growth curve model shows similar performance with power function model. In conclusion, the growth curve model can be applied in the estimation of the software cost.