• Journal of Information Technology Services
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• v.11 no.3
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• pp.89-101
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• 2012

The study investigated if IT investment in Korean financial markets for the past 18 years has grown following the s-curve pattern based on Nolan's growth model in order to find the correlation between IT investment and management performance in the financial industry. According to the research finding it can be said that the overall financial markets maintain s-curve pattern, and IT investment is related to management performance, particularly increase in total assets and net profit. However, each sector has defining features of growth patterns. The banking industry has grown similarly to the s-curve, and the insurance industry also shows the s-curve but it looks more like linear pattern. In terms of securities industry, its growth patterns can hardly be considered s-curve due to the irregular changes. his research outcome illustrates the analysis of IT growth patterns in the financial industry and thus, it is expected to be a useful reference when deciding the appropriate time for IT investment in the financial industry.

• Phonetics and Speech Sciences
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• v.9 no.3
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• pp.17-23
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• 2017

The present study investigates the effect of Accentual Phrase on F0 using a subset of large-scale corpus of Seoul Korean. Four syllable words which were neither preceded nor followed by silent pauses were presumed to be canonical exemplars of Accentual Phrases in Korean. These four syllable words were extracted from female speakers' speech samples. Growth curve analyses, combination of regression and polynomial curve fitting, were applied to the four syllable words. Four syllable words were divided into four groups depending on the categorical status of the initial segment: voiceless obstruents, voiced obstruents, sonorants, and vowels. Results of growth curve analyses indicate that initial segment types have an effect on the F0 (in semitone) in the nucleus of the initial syllable, and the cubic polynomial term revealed that some of the medial low tones in the 4 syllable words may be guided by the principle of contrast maximization, while others may be governed by the principle of ease of articulation.

• Journal of Environmental Science International
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• v.31 no.9
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• pp.793-801
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• 2022

This study was carried out to provide basic data for logical forest management by developing a site index curve reflecting the current growth characteristics of Cryptomeria japonica stands in Korea. The height growth model was developed using the Chapman-Richards, Schumacher, Gompertz, and Weibull algebraic difference equations, which are widely used in growth estimation, for data collected from 119 plots through the 7th National Forest Inventory and stand survey. The Chapman-Richards equation, with the highest model fit, was selected as the best equation for the height growth model, and a site index curve was developed using the guide curve method. To compare the developed site index curve with that on the yield table, paired T-tests with a significance level of 5% were performed. The results indicated that there were no significant differences between the site index curve values at all ages, and the p-value was smaller after the reference age than before. Therefore, the site index curve developed through this study reflects the characteristics of the changing growth environment of C. japonica stands and can be used in accordance with the site index curve on the current yield table. Thus, this information can be considered valuable as basic data for reasonable forest management.

• The KIPS Transactions:PartD
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• v.11D no.7 s.96
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• pp.1451-1458
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• 2004

Current software reliability growth models based on Gompertz growth curve are all logarithmic type. Software reliability growth models based on logarithmic type Gompertz growth curve has difficulties in parameter estimation. Therefore this paper proposes a software reliability growth model based on the logistic type Gompertz growth curie. Its usefulness is empirically verified by analyzing the failure data sets obtained from 13 different software projects. The parameters of model are estimated by linear regression through variable transformation or Virene's method. The proposed model is compared with respect to the average relative prediction error criterion. Experimental results show that the pro-posed model performs better the models based on the logarithmic type Gompertz growth curve.

• Journal of Advanced Marine Engineering and Technology
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• v.29 no.8
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• pp.855-861
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• 2005

Fracture toughness defined near the initiation of stable crack growth is investigated by R-curve and Direct Current electric Potential Determination(DCPD) under mode I plane strain conditions for CT specimen with 25.4mm thickness of SS400 steel. Fracture toughness. $J_{IC}$lit near crack tip of CT specimen by R-curve is 17.14 $kg_{f}/mm$ and however. its value by DCPD is 22.82 $Rg_{f} mm$ The value of fracture toughness by DCPD is larger than that by R-curve. Therefore, it is suggested that the evaluation of fracture toughness by R-curve is optimum than by DCPD, when considering amount of crack growth about each of fracture toughness.

• Transactions of the Korean Society of Mechanical Engineers
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• v.13 no.5
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• pp.928-937
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• 1989

Applicability of $T_{\delta}$ proposed by Shin et al as an instability parameter for ductile material is investigated, Both general fracture test and instability fracture test are performed using compact tension specimens of structural alloy steel(SCM4), The values of ( $T_{\delta}$)$_{app}$(applied tearing modules) estimated from the real load vs. crack growth curve measured from experiments are compared with those estimated from the limit load vs. crack growth curve. The results are:(1) the $T_{\delta}$ parameter may be used as a crack instability parameter:(2) the use of ( $T_{\delta}$)$_{app}$ estimated from the load-crack growth curve, proposed in this study is reasonably justified.ified.d.

• IE interfaces
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• v.23 no.3
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• pp.205-212
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• 2010

The learning curve model is a mathematical form which represents the relationship between the manufacturing experience and its effectiveness. The semiconductor manufacturing is widely known as an appropriate example for the learning effect due to its complicated manufacturing processes. In this paper, I propose a new compound learning curve model for semiconductor products in which the general learning curve model and the growth curve are composed. The dependent variable and the effective independent variables of the model were abstracted from the existing learning curve models and selected according to multiple regression processes. The simulation results using the historical DRAM data show that the proposed compound learning curve model is one of adequate models for describing learning effect of semiconductor products.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.9
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• pp.1252-1258
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• 2015

The Liangshan pig is a traditional Chinese small-sized breed; it has a relatively long feeding period and low meat production ability but superior meat quality. This study utilized three non-linear growth models (Von Bertalanffy, Gompertz, and logistic) to fit the growth curve of Liangshan pigs from an unselected, random-bred pig population and estimate the pigs most suitable slaughter weight. The growth development data at 20 time points of 275 Liangshan pigs (from birth to 250 d) were collected. To analyze the relative gene expression related to development, seven slaughter weight phases (50, 58, 66, 74, 82, 90, and 98 kg) (20 pigs per phase) were examined. We found that the Liangshan pig growth curve fit the typical S-curve well and that their growth turning point was 193.4 days at a weight of 62.5 kg, according to the best fit Von Bertalanffy model based on the goodness of fit criteria. Furthermore, we estimated that the most suitable slaughter weight was 62.5 to 74.9 kg based on the growth curve and the relative expression levels of growth-related genes.

• Journal of the Korean Data and Information Science Society
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• v.10 no.2
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• pp.369-385
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• 1999

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 likelihood ratio testing statistics in mean shift model is established and its distribution is derived. After we detected 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 Korean Society for Quality Management
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• v.23 no.2
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• pp.53-67
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• 1995

The problem considered here is to find the optimal discriminant analysis method in growth curve model. It has been studied how to find correct prior probability for the effective classification in discriminant analysis. We use the balanced condition to calculate prior probability. From the informative simulation study, new classification rule for the growth curve model is suggested. The suggested classification rule has better classification result than the other previously suggested method in terms of error rate criterion.