• International journal of advanced smart convergence
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• v.12 no.1
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• pp.157-163
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• 2023

The current research aims to examine the moderating effect of consumers' mindset on their product purchase intention in the multi-promotion offers containing both a bonus pack and a price discount (i.e., BP + PD offers). That is, this research investigateswhether consumers' product purchase intention in the BP + PD offers variesdepending on their mindset (growth mindset vs. fixed mindset). Specifically, it is predicted that consumers with a fixed mindset will have higher product purchase intention in the offers containing the high PD but low extra amount of BP (LBP HPD) than in the offers with a high extra amount of BP but low PD (HBP LPD), whereas consumers with a growth mindset will have higher product purchase intention in the HBP LPD offers than in the LBP HPD offers. An experiment wasconducted to test the prediction. Consistent with the prediction, it was found that participants' mindset moderates their product purchase intention in multi-promotion offers. The findings imply that marketers can evoke more positive consumer purchase intention toward BP and PD offers, considering consumer mindset.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.58-58
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• 2022

With the development of advanced technology, automation of agricultural work is spreading. In association with the 4th industrial revolution-based technology, research on field smart farm technology is being actively conducted. A state-of-the-art unmanned automated agricultural production demonstration complex was established in Naju-si, Jeollanam-do. For the operation of the demonstration area platform, it is necessary to build a sophisticated, advanced, and intelligent field smart farming model. For the operation of the unmanned automated agricultural production demonstration area platform, we are building data on the growth of soybean for smart cultivated crops and conducting research to determine the optimal time for agricultural work. In order to operate an unmanned automation platform, data is collected to discover digital factors for water management immediately after planting, water management during the growing season, and determination of harvest time. A subsurface drip irrigation system was established for smart water management. Irrigation was carried out when the soil moisture was less than 20%. For effective water management, soil moisture was measured at the surface, 15cm, and 30cm depth. Vegetation indices were collected using drones to find key factors in soybean production prediction. In addition, major growth characteristics such as stem length, number of branches, number of nodes on the main stem, leaf area index, and dry weight were investigated. By discovering digital factors for effective decision-making through data construction, it is expected to greatly enhance the efficiency of the operation of the unmanned automated agricultural production demonstration area.

• Journal of the Korea Institute of Military Science and Technology
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• v.5 no.4
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• pp.67-77
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• 2002

This paper introduces the calibration results of the fatigue crack growth models for damage tolerance analysis of the aircraft structures. Generalized Willenborg model and Wheeler model are calibrated with experimental data tested under the load spectrum of a trainer. The retardation factors such as, shut-off ratio in Generalized Willenborg model and shaping exponent in Wheeler model, are evaluated for aluminum alloys AL2024-T3511, AL7050-T7451 and AL7075-T73511. It is shown that the retardation effect of the crack growth rate depends on the yield strength of material and the maximum stress in the load spectrum. Generalized Willenborg model and Wheeler model give satisfactory prediction of crack growth life but the calibration of the experimental parameters with test is required.

• Nuclear Engineering and Technology
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• v.48 no.4
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• pp.1036-1046
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• 2016

We propose a primary water stress corrosion cracking (PWSCC) initiation model of Alloy 600 that considers the stress triaxiality factor to apply to finite element analysis. We investigated the correlation between stress triaxiality effects and PWSCC growth behavior in cold-worked Alloy 600 stream generator tubes, and identified an additional stress triaxiality factor that can be added to Garud's PWSCC initiation model. By applying the proposed PWSCC initiation model considering the stress triaxiality factor, PWSCC growth simulations based on the macroscopic phenomenological damage mechanics approach were carried out on the PWSCC growth tests of various cold-worked Alloy 600 steam generator tubes and compact tension specimens. As a result, PWSCC growth behavior results from the finite element prediction are in good agreement with the experimental results.

• Journal of Digital Convergence
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• v.18 no.2
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• pp.205-211
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• 2020

The method of predicting the future may be predicted by technical characteristics or technical performance. Therefore, technology prediction is used in the field of strategic research that can produce economic and social benefits. In this study, we predicted the future market through the study of how to predict the future with these technical characteristics. The future prediction method was studied through the prediction of the time when the market occupied according to the demand of special product. For forecasting market demand, we proposed the future forecasting model through comparison of representative quantitative analysis methods such as CAGR model, BASS model, Logistic model and Gompertz Growth Curve. This study combines Rogers' theory of innovation diffusion to predict when products will spread to the market. As a result of the research, we developed a methodology to predict when a particular product will mature in the future market through the spread of various factors for the special product to occupy the market. However, there are limitations in reducing errors in expert judgment to predict the market.

• Animal Bioscience
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• v.36 no.7
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• pp.1003-1009
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• 2023

Objective: The objective was to compare (pedigree-based) best linear unbiased prediction (BLUP), genomic BLUP (GBLUP), and single-step GBLUP (ssGBLUP) methods for genomic evaluation of growth traits in a Mexican Braunvieh cattle population. Methods: Birth (BW), weaning (WW), and yearling weight (YW) data of a Mexican Braunvieh cattle population were analyzed with BLUP, GBLUP, and ssGBLUP methods. These methods are differentiated by the additive genetic relationship matrix included in the model and the animals under evaluation. The predictive ability of the model was evaluated using random partitions of the data in training and testing sets, consistently predicting about 20% of genotyped animals on all occasions. For each partition, the Pearson correlation coefficient between adjusted phenotypes for fixed effects and non-genetic random effects and the estimated breeding values (EBV) were computed. Results: The random contemporary group (CG) effect explained about 50%, 45%, and 35% of the phenotypic variance in BW, WW, and YW, respectively. For the three methods, the CG effect explained the highest proportion of the phenotypic variances (except for YW-GBLUP). The heritability estimate obtained with GBLUP was the lowest for BW, while the highest heritability was obtained with BLUP. For WW, the highest heritability estimate was obtained with BLUP, the estimates obtained with GBLUP and ssGBLUP were similar. For YW, the heritability estimates obtained with GBLUP and BLUP were similar, and the lowest heritability was obtained with ssGBLUP. Pearson correlation coefficients between adjusted phenotypes for non-genetic effects and EBVs were the highest for BLUP, followed by ssBLUP and GBLUP. Conclusion: The successful implementation of genetic evaluations that include genotyped and non-genotyped animals in our study indicate a promising method for use in genetic improvement programs of Braunvieh cattle. Our findings showed that simultaneous evaluation of genotyped and non-genotyped animals improved prediction accuracy for growth traits even with a limited number of genotyped animals.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1045-1050
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• 2003

In this study, to investigate the effects of omitting low-amplitude cycles from a flight-simulation loading, crack growth tests are conducted on 2124-T851 aluminum alloy specimens. Three test spectra are generated by omitting small load ranges as counted by the rain-flow count method. The crack growth test results are compared with the data obtained from the flight-simulation loading. The experimental results show that omission of the load ranges below 5% of the maximum load does not significantly affect crack growth behavior, because these are below the initial stress intensity factor range. However, in the case of omitting the load ranges below 15% of the maximum load, crack growth rates decrease, and therefore crack growth curve deviates from the crack growth data under the flight-simulation loading. To optimize the load range that can be omitted, crack growth curves are simulated by the stochastic crack growth model. The prediction shows that the omission level can be extended to 8% of the maximum load and test time can be reduced by 59%.

• The Journal of Pediatrics of Korean Medicine
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• v.31 no.4
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• pp.31-38
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• 2017

Objectives The purpose of this study was to find out the clinically reliable relationships between the Risser sign and chronological age, bone age, menarche, and adult height prediction (AHP) and to evidence the reliability of the Risser sign. Methods This study had been carried out with 50 children who had their growth checked in an oriental medical hospital from January 2015 to February 2017. We investigated Risser sign in AP X-rays with iliac crest, bone age, AHP for all 50 children and the timing of menarche from the 22 girls in the study subjects. We also investigated a correlation between the Risser stage and the other indicators to analyze statistical data. Results The mean chronological ages of Risser 1, 2, 3 and 4 were 11.2, 12.6, 14.4, and 15.5 years respectively for the boys and 10.8, 12.2, 13.8 and 14.8 years respectively for the girls. The mean bone ages of Risser 1, 2, 3 and 4 were 12.3, 13.6, 15.7 and 16.5 years respectively for the boys and 11.7, 13.8, 14.3 and 14.9 years respectively for the girls. We analyzed 22 girls' Risser stages in accordance with the duration from menarche. The result showed that in the first six months after menarche, all girls were in Risser 1 and 2; in the next six months, the girls were in Risser 2 on average; in the next 12 months, all girls were in Risser 3 and 4; after more than two years from menarche, all girls were in Risser 4. The mean remaining growth height of Risser 1, 2, 3 and 4 were 27.8, 17.3, 4.4 and 1.0 cm respectively for the boys and 14.5, 5.1, 3.1 and 1.1 cm respectively for the girls. The Risser stage was correlated strongly with chronological age (Spearman's rho=0.707 (boy), 0.841 (girl)), bone age (Spearman's rho=0.869 (boy), 0.875 (girl)), duration from menarche (Spearman's rho=0.909) and remaining growth height (Spearman's rho=-0.784 (boy), -0.878 (girl)). Conclusions This study showed that the Risser sign can be useful in assessing skeletal maturity and predicting remaining growth height based on the Risser stage and the other growth indicators.

• Journal of Digital Contents Society
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• v.19 no.6
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• pp.1105-1114
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• 2018

The growth rate of the domestic digital music contents market has been remarkable recently. Accordingly, the necessity of prediction for chart success of digital music contents has grown. This paper proposes prediction indexes for chart success of digital music contents through analysis of correlation between social data such as Internet news, SNS and entry rankings in Melon's weekly music charts. We collected a total of 10 social data items for each male and female artist, and executed cluster analysis. Through this, we found meaningful prediction indexes for chart success of digital music contents for each male and female artist.

• Asian-Australasian Journal of Animal Sciences
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• v.12 no.6
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• pp.850-853
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• 1999

Angus postweaning daily gain (PWDG) was analyzed to investigate effects of the heterogeneous variance and the genotypes by sex interaction on prediction of EBVs with data sets of various environmental levels. A whole data (16,239 records) was divided into six data sets according to averages of the best linear unbiased estimator (BLUE) of herd environment. The results comparing prediction models showed that single-trait model is adequate for most of the data sets except for the data set of poor environment for both of the bulls and the heifers where the heterogeneity of variance and the genotypes by sex interaction exists. In the prediction with the data set of the low environment level, the bull's EBVs by single-trait models had high product moment correlations with male EBVs of the bulls by the multitrait model. Whereas the heifer's EBVs had moderate correlations with female EBVs by the multitrait model. This moderate correlation seems to be resulted by the heterogeneity of variance and low heritability of the heifer's PWDG. The prediction models with heterogeneity of variance had little effect on the prediction of EBVs for the data sets with moderate to high genetic correlations.