• Korean Journal of Plant Resources
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• v.20 no.1
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• pp.7-11
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• 2007

This study was conducted by estimate of leaf characteristics and growth performance among selected 20 families progenies of Hovenia dulcis var. koreana Nakai. Mean seedling height and root-collar diameter in whole progenies showed 61.6cm, 6.98mm, respectively. Mean seedling height of KW 2-5 family was 79.3cm and it was higher than that of other families. JN 2-2 family had highest value, 9.16mm, in mean of root-collar diameter. Growth performances of KW 2-5 and JN 2-2 families showed 57% (in seedling height), 53% (in root-collar diameter) superior to those of lowest marked families. The selection level based on growth performances, which are seedling height over 75.0cm and root-collar diameter over 8.0mm, were applied on whole families, and two families selected (KW 2-5, JN 2-2). The selection effects from selected families was evaluated as 125% compared to the mean of whole families. The coefficient of variation (C.V) appeared wide range, $9.4{\sim}42.4%$, in estimated leaf characteristics. Particularly, C.V of petiole length (PL) and petiole diameter (PD) showed 42.4% and 28.7%, respectively. Their were higher value than other leaf characteristics. Analysis of variance for all leaf characteristics were significantly different among families. Also, there had positive correlation between most leaf characteristics except the correlation between leaf length (LL) and leaf morphological index (LMI, LW/LL). Particularly, the correlation between leaf length and leaf width (LW) showed the highest correlation.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.3
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• pp.303-310
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• 2015

The study was conducted to analyze the genetic parameters of somatic cell score (SCS) of Holstein cows, which is an important indicator to udder health. Test-day records of somatic cell counts (SCC) of 305-day lactation design from first to fifth lactations were collected on Holsteins in Korea during 2000 to 2012. Records of animals within 18 to 42 months, 30 to 54 months, 42 to 66 months, 54 to 78 months, and 66 to 90 months of age at the first, second, third, fourth and fifth parities were analyzed, respectively. Somatic cell scores were calculated, and adjusted for lactation production stages by Wilmink's function. Lactation averages of SCS ($LSCS_1$ through $LSCS_5$) were derived by further adjustments of each test-day SCS for five age groups in particular lactations. Two datasets were prepared through restrictions on number of sires/herd and dams/herd, progenies/sire, and number of parities/cow to reduce data size and attain better relationships among animals. All LSCS traits were treated as individual trait and, analyzed through multiple-trait sire models and single trait animal models via VCE 6.0 software package. Herd-year was fitted as a random effect. Age at calving was regressed as a fixed covariate. The mean LSCS of five lactations were between 3.507 and 4.322 that corresponded to a SCC range between 71,000 and 125,000 cells/mL; with coefficient of variation from 28.2% to 29.9%. Heritability estimates from sire models were within the range of 0.10 to 0.16 for all LSCS. Heritability was the highest at lactation 2 from both datasets (0.14/0.16) and lowest at lactation 5 (0.11/0.10) using sire model. Heritabilities from single trait animal model analyses were slightly higher than sire models. Genetic correlations between LSCS traits were strong (0.62 to 0.99). Very strong associations (0.96 to 0.99) were present between successive records of later lactations. Phenotypic correlations were relatively weaker (<0.55). All correlations became weaker at distant lactations. The estimated breeding values (EBVs) of LSCS traits were somewhat similar over the years for a particular lactation, but increased with lactation number increment. The lowest EBV in first lactation indicated that selection for SCS (mastitis resistance) might be better with later lactation records. It is expected that results obtained from these multi-trait lactation model analyses, being the first large scale SCS data analysis in Korea, would create a good starting step for application of advanced statistical tools for future genomic studies focusing on selection for mastitis resistance in Holsteins of Korea.

• Korean Journal of Environmental Biology
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• v.37 no.3
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• pp.380-388
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• 2019

The studies regarding soil bacterial community and correlation analysis of wild-simulated ginseng cultivation area are insufficient. The purpose of this study was to investigate the correlation between soil bacterial community and growth characteristics of wild-simulated ginseng for selection of suitable cultivation area. The bacterial community was investigated by high throughput sequencing technique (Illumina platform). The correlation coefficient between soil bacterial community and growth characteristics were analyzed using Spearman's rank correlation. The soil bacterial community from soil samples of 8 different wild-simulated ginseng cultivated area exhibited two distinct clusters, cluster 1 and cluster 2. The relative abundance of Proteobacteria (35.4%) and Alphaproteobacteria(24.4%) was observed to be highest in all soil samples. The lower soil pH and higher abundance of Acidobacteria resulted in increased growth of wild-simulated ginseng. Additionally, abundance of Acidobacteriia (class) and Koribacteraceae (family) demonstrated significant positive correlation with fresh weight of wild-simulated ginseng. The results of this study clearly state the correlation between growth characteristic and soil bacterial community of wild-simulated ginseng cultivation area, thereby offering effective insight into selection of suitable cultivation area of wild-simulated ginseng.

• Journal of Gifted/Talented Education
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• v.17 no.2
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• pp.307-337
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• 2007

The purpose of this study is to verify the validity of a creativity measurement tool and to discover the creativity characteristics of creative gifted students by assessing the difference in the creativity characteristics of creative gifted students, who were selected from gifted students in elementary and middle schools through the Torrance Test of Creative Thinking(TTCT), according to school level and the type of the students (gifted student in mathematics, gifted student in science). To this research purpose, creative gifted students were selected by the Torrance Test of Creative Thinking(TTCT) on 594 students, who had applied for super gifted education, from 17 gifted students institutes under the jurisdiction of Jeollabukdo office of education, Then, t-tests and multiple regression analysis were performed to analyze the creativity factors between elementary students and middle school students and between mathematics-gifted students and science-gifted students. From the research, the following results were obtained. Although TTCT is effective in distinguishing gifted students with and without creativity, correlation coefficient values between creativity factors(the correlation coefficients between 'fluency' and 'originality' and between 'fluency' and 'elaboration' were .78 and .50 respectively) suggested the possibility of low uniqueness of creativity factors. In addition, compared with elementary students, middle school students showed significantly lower fluency (circles), elaboration(picture construction, picture completion), and the abstractness of titles(picture structure). In the meantime, science-gifted students displayed significantly higher originality(picture construction), and elaboration(picture construction, picture completion, circles) than mathematics-gifted students. Therefore, continuous study is required to enhance the validity of the test for the selection of creativity gifted students. Besides, efforts should be made to find ways to enhance the creativity of gifted students and to resolve the problem of decreasing creativity with student academic level increasing.

• Tunnel and Underground Space
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• v.30 no.3
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• pp.214-225
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• 2020

Uniaxial compressive strength (UCS) of rock is one of the important factors to determine the advance speed during shield TBM tunnel excavation. UCS can be obtained through the Geotechnical Data Report (GDR), and it is difficult to measure UCS for all tunneling alignment. Therefore, the purpose of this study is to predict UCS by utilizing TBM machine driving data and machine learning technique. Several machine learning techniques were compared to predict UCS, and it was confirmed the stacking model has the most successful prediction performance. TBM machine data and UCS used in the analysis were obtained from the excavation of rock strata with slurry shield TBMs. The data were divided into 8:2 for training and test and pre-processed including feature selection, scaling, and outlier removal. After completing the hyper-parameter tuning, the stacking model was evaluated with the root-mean-square error (RMSE) and the determination coefficient (R²), and it was found to be 5.556 and 0.943, respectively. Based on the results, the sacking models are considered useful in predicting rock strength with TBM excavation data.

• Journal of Life Science
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• v.8 no.4
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• pp.437-442
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• 1998

Seed and leaf size is the important morphological traits considered by plant breeder and is the important yield components in soybean. The objective of this research was to know the relationship between seed size and leaf size in 66 $F_2$ populations derived from half diallel mating system with 12 soybean strains, representing distinct seed and leaf size. The range of seed size for 12 parents used was 6.7 to 43.8 g/100 seed. Leaf width leaf length ranged 5.7 to 8.6 cm and 9.4 to 12.9 cm, respectively. Leaf width was highly correlated with leaf length with an R square of 0.754 in the $F_2$ generation. The $F_2$ regression` coefficient indicated that leaves were, on average 1.4 times greater length than in width . Leaf size (width) was highly correlated (r.0.91) with seed size (g/100 seed) in the $F_2$ generation with an R square of 0.833. Our results indicate postive correlation within seed and leaf size is common in $F_2$ segregating populations derived from crossing with soybean. The strong liner relationship we observed between leaf size and seed size in $F_2$ segragating population is useful in that in that indirect selection for a secondary character may be superior to direct selection for the primary character.

• Journal of the Korean GEO-environmental Society
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• v.10 no.1
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• pp.49-54
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• 2009

The seismic slope stability is most often evaluated by the pseudo-static limit analysis, in which the earthquake loading is simplified as static inertial loads acting in horizontal and/or vertical directions. The transient loading is represented by constant acceleration via the pseudostatic coefficients. The result of a pseudostatic analysis is governed by the selection of the value of the pseudostatic coefficient. However, selection of the value is very difficult and often done in an ad hoc manner without a sound physical reasoning. In addition, the maximum acceleration is commonly estimated from the design guideline, which cannot accurately estimate the dynamic response of a slope. There is a need to perform a 2D dynamic analysis to properly define the dynamic response characteristics. This paper develops a new hybrid pseudostatic method that links the modified one-dimensional seismic site response analysis and the pseudostatic algorithm. The modified site response analysis adjusts the density of the layers to simulate the change in mass and weight of the layers of the slope with depth. Multiple analyses were performed at various locations within the slope to estimate the change in seismic response of the slope. The calculated peak acceleration profiles with depth from the developed procedure were compared to those by the two-dimensional analyses. Comparisons show that the two methods result in remarkable match. The calculated profiles are used to perform pseudostatic analysis. The results show that use of peak or a fraction of acceleration at the surface can seriously underestimate or overestimate the factor of safety, and that the proposed procedure significantly enhances the reliability of a standard procedure.

• Korean Journal of Plant Resources
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• v.32 no.5
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• pp.463-470
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• 2019

Wild-simulated ginseng is requires standard establishment on location environment for long-term and eco-friendly cultivation. The this study was carried out to investigate the correlation between growth characteristics and location environment of wild-simulated ginseng for selection of suitable cultivation area. Samples were collected from a 9 site of wild-simulated cultivation area and examined growth characteristics and location environment. Correlation coefficient between growth characteristics and location environment was analyzed using Spearman's rank correlation. The growth of wild-simulated ginseng was shown significantly higher in Geochang and Hamyang cultivation area. The results of correlation analysis was shown significantly correlation with percentage of conifer, total diameter at breast height, soil pH, K, Ca and Mg. The results of this study was clearly investigated the correlation between growth characteristics and location environment of wild-simulated ginseng, which is considered to will provide understanding for selection suitable cultivation area of wild-simulated ginseng.

• Korean Journal of Radiology
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• v.23 no.8
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• pp.811-820
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• 2022

Objective: To develop a model incorporating radiomic features and clinical factors to accurately predict acute ischemic stroke (AIS) outcomes. Materials and Methods: Data from 522 AIS patients (382 male [73.2%]; mean age ± standard deviation, 58.9 ± 11.5 years) were randomly divided into the training (n = 311) and validation cohorts (n = 211). According to the modified Rankin Scale (mRS) at 6 months after hospital discharge, prognosis was dichotomized into good (mRS ≤ 2) and poor (mRS > 2); 1310 radiomics features were extracted from diffusion-weighted imaging and apparent diffusion coefficient maps. The minimum redundancy maximum relevance algorithm and the least absolute shrinkage and selection operator logistic regression method were implemented to select the features and establish a radiomics model. Univariable and multivariable logistic regression analyses were performed to identify the clinical factors and construct a clinical model. Ultimately, a multivariable logistic regression analysis incorporating independent clinical factors and radiomics score was implemented to establish the final combined prediction model using a backward step-down selection procedure, and a clinical-radiomics nomogram was developed. The models were evaluated using calibration, receiver operating characteristic (ROC), and decision curve analyses. Results: Age, sex, stroke history, diabetes, baseline mRS, baseline National Institutes of Health Stroke Scale score, and radiomics score were independent predictors of AIS outcomes. The area under the ROC curve of the clinical-radiomics model was 0.868 (95% confidence interval, 0.825-0.910) in the training cohort and 0.890 (0.844-0.936) in the validation cohort, which was significantly larger than that of the clinical or radiomics models. The clinical radiomics nomogram was well calibrated (p > 0.05). The decision curve analysis indicated its clinical usefulness. Conclusion: The clinical-radiomics model outperformed individual clinical or radiomics models and achieved satisfactory performance in predicting AIS outcomes.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.2
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• pp.133-140
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• 2016

Software reliability in the software development process is an important issue. Software process improvement helps in finishing with reliable software product. Infinite failure NHPP software reliability models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, we were proposed the reliability model with the exponential and inverse exponential distribution, which made out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on mean square error (MSE) and coefficient of determination($R^2$), for the sake of efficient model, were employed. Analysis of failure, using real data set for the sake of proposing the exponential and inverse exponential distribution, was employed. This analysis of failure data compared with the exponential and inverse exponential distribution property. In order to insurance for the reliability of data, Laplace trend test was employed. In this study, the inverse exponential distribution model is also efficient in terms of reliability because it (the coefficient of determination is 80% or more) in the field of the conventional model can be used as an alternative could be confirmed. From this paper, the software developers have to consider life distribution by prior knowledge of the software to identify failure modes which can be able to help.