• 한국약용작물학회지
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• 제17권3호
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• pp.198-203
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• 2009

Isatis tinctoria var. yezoensis (Ohwi) Ohwi (Cruciferae) is one of major natural dyeing crops in the world and also have used as a medicinal plant in Korea. We evaluated seed purity in $F_1$-hybrid accessions using amplified fragment length polymorphism (AFLP) markers. One hundred sixty seeds from the male and female harvests were subsequently screened for seed purity with ten primers. The 13 accession-specific bands and many variable AFLP bands scored for accessions. Especially, E-AAC/M-CAA and E-AAG/M-CAT were presented clear hybrid bands for $F_1$ hybrids. $F_1$ hybrids maintained higher average level of genetic diversity compared with their correspondent parents. Self-inbred seeds from the female and male harvests were revealed 8.0% and 5.0%, respectively. The AFLP may lead to a better insight in to the hybrid seed purity test in I. tinctoria var. yezoensis.

• 한국육종학회지
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• 제43권4호
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• pp.273-281
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• 2011

Fusarium head blight (FHB), also known as scab, caused mainly by Fusarium graminearum is a devastating disease of wheat in regions that are warm and humid during flowering. In addition to significant yield and quality losses, the mycotoxin deoxynivalenol produced by the pathogen in infected wheat kernels is a serious problem for food and feed safety. Twenty- three Korean cultivars and "Sumai 3", which is a FHB-resistant Chinese cultivar were tested for Type I, Type II resistances of FHB. Three cultivars were identified as resistant in Type I assessment, and two cultivars were resistant in Type II assessment. Genetic variation and relationship among the cultivars were evaluated on the basis of 11 Simple Sequence Repeat (SSR) and 29 Sequence Tagged Site (STS) markers that were linked to FHB resistance Quantitative Trait Loci (QTL) on chromosome 3BS. One SSR and 7 STS markers detected polymorphisms. Especially, using a STS marker (XSTS3B-57), 32.4% of the variation for Type II FHB resistance could be explained. Genetic relationship among Korean wheat cultivars was generally consistent with their released year. These markers on chromosome 3BS have the potential for accelerating the development of Korean wheat cultivars with improved Fusarium head blight resistance through the use of marker-assisted selection.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.448-448
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• 2018

In this study, the regression models (Load ESTimator and eight-parameter model) were evaluated to estimate instantaneous pollutant loads under various criteria and optimization methods. As shown in the results, LOADEST commonly used in interpolating pollutant loads could not necessarily provide the best results with the automatic selected regression model. It is inferred that the various regression models in LOADEST need to be considered to find the best solution based on the characteristics of watersheds applied. The recently developed eight-parameter model integrated with Genetic Algorithm (GA) and Gradient Descent Method (GDM) were also compared with LOADEST indicating that the eight-parameter model performed better than LOADEST, but it showed different behaviors in calibration and validation. The eight-parameter model with GDM could reproduce the nitrogen loads properly outside of calibration period (validation). Furthermore, the accuracy and precision of model estimations were evaluated using various criteria (e.g., $R^2$ and gradient and constant of linear regression line). The results showed higher precisions with the $R^2$ values closed to 1.0 in LOADEST and better accuracy with the constants (in linear regression line) closed to 0.0 in the eight-parameter model with GDM. In hence, based on these finding we recommend that users need to evaluate the regression models under various criteria and calibration methods to provide the more accurate and precise results for pollutant load estimations.

• Geomechanics and Engineering
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• 제19권2호
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• pp.127-139
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• 2019

Available methods to determine the ultimate bearing capacity of shallow foundations may not be accurate enough owing to the complicated failure mechanism and diversity of the underlying soils. Accordingly, applying new methods of artificial intelligence can improve the prediction of the ultimate bearing capacity. The M5' model tree and the genetic programming are two robust artificial intelligence methods used for prediction purposes. The model tree is able to categorize the data and present linear models while genetic programming can give nonlinear models. In this study, a combination of these methods, called the M5'-GP approach, is employed to predict the ultimate bearing capacity of the shallow foundations, so that the advantages of both methods are exploited, simultaneously. Factors governing the bearing capacity of the shallow foundations, including width of the foundation (B), embedment depth of the foundation (D), length of the foundation (L), effective unit weight of the soil (${\gamma}$) and internal friction angle of the soil (${\varphi}$) are considered for modeling. To develop the new model, experimental data of large and small-scale tests were collected from the literature. Evaluation of the new model by statistical indices reveals its better performance in contrast to both traditional and recent approaches. Moreover, sensitivity analysis of the proposed model indicates the significance of various predictors. Additionally, it is inferred that the new model compares favorably with different models presented by various researchers based on a comprehensive ranking system.

• Nuclear Engineering and Technology
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• 제39권4호
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• pp.337-348
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• 2007

A fuzzy neural network model is presented to predict residual stress for dissimilar metal welding under various welding conditions. The fuzzy neural network model, which consists of a fuzzy inference system and a neuronal training system, is optimized by a hybrid learning method that combines a genetic algorithm to optimize the membership function parameters and a least squares method to solve the consequent parameters. The data of finite element analysis are divided into four data groups, which are split according to two end-section constraints and two prediction paths. Four fuzzy neural network models were therefore applied to the numerical data obtained from the finite element analysis for the two end-section constraints and the two prediction paths. The fuzzy neural network models were trained with the aid of a data set prepared for training (training data), optimized by means of an optimization data set and verified by means of a test data set that was different (independent) from the training data and the optimization data. The accuracy of fuzzy neural network models is known to be sufficiently accurate for use in an integrity evaluation by predicting the residual stress of dissimilar metal welding zones.

• Journal of Interdisciplinary Genomics
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• 제1권1호
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• pp.10-13
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• 2019

A 10-year and 5 month-old girl with developmental delay, intellectual disability, attention deficit hyperactivity disorder, poor weight gain, and microcephaly was transferred to our pediatric clinic for genetic evaluation. Her height was within the 5-10th percentile, and her weight was under the 3rd percentile. On the social maturity scale, her developmental status was scored as 3 years 9 months for social age, and the social quotient was 35.98. A chromosomal microarray analysis was performed and the microduplication at chromosome 16p was observed: arr[GRCh37] 16p11.2 (29580020_30190029)${\times}3$. Currently, the patient is diagnosed with Grade 2 intellectual disability and is attending a computerized cognitive rehabilitation class twice weekly. In addition, nutritional support and growth follow up are also ensured in the Pediatric Gastrointestinal and Endocrinology clinic.

• 한국구조물진단유지관리공학회 논문집
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• 제23권4호
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• pp.53-60
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• 2019

이 연구에서는 정적 변위를 사용하는 유전자 알고리즘을 이용한 교량의 유한요소해석모델 개선 기법을 제안하며, PSC 거더교를 대상으로 한 실증시험 데이터를 이용하여 제안된 방법을 검증하였다. 실증 재하시험으로 정적재하시험과 의사정적재하시험을 수행하였으며, 각 재하시험의 계측 데이터를 이용하여 대상교량의 유한요소해석모델 개선을 진행하였다. 최종적으로 의사정적재하시험의 계측 데이터를 통해 개선된 모델을 이용하여 공용 내하력평가를 수행하였다. 내하력평가에는 현 도로교설계기준과 구 도로교설계기준, AASHTO LRFD의 설계 활하중을 이용하였으며, 각 설계기준 별 내하력평가 결과를 비교하였다.

• Genomics & Informatics
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• 제20권2호
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• pp.17.1-17.11
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• 2022

Genetic associations have been quantified using a number of statistical measures. Entropy-based mutual information may be one of the more direct ways of estimating the association, in the sense that it does not depend on the parametrization. For this purpose, both the entropy and conditional entropy of the phenotype distribution should be obtained. Quantitative traits, however, do not usually allow an exact evaluation of entropy. The estimation of entropy needs a probability density function, which can be approximated by kernel density estimation. We have investigated the proper sequence of procedures for combining the kernel density estimation and entropy estimation with a probability density function in order to calculate mutual information. Genotypes and their interactions were constructed to set the conditions for conditional entropy. Extensive simulation data created using three types of generating functions were analyzed using two different kernels as well as two types of multifactor dimensionality reduction and another probability density approximation method called m-spacing. The statistical power in terms of correct detection rates was compared. Using kernels was found to be most useful when the trait distributions were more complex than simple normal or gamma distributions. A full-scale genomic dataset was explored to identify associations using the 2-h oral glucose tolerance test results and γ-glutamyl transpeptidase levels as phenotypes. Clearly distinguishable single-nucleotide polymorphisms (SNPs) and interacting SNP pairs associated with these phenotypes were found and listed with empirical p-values.

• 한국동물생명공학회지
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• 제37권2호
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• pp.106-112
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• 2022

Cryopreservation of porcine ovarian tissue by vitrification method is a promising approach to preserve genetic materials for future use. However, information is not enough and technology still remains in a challenge stage in pig. Therefore, the objective of present study was to determine possibility of vitrification method to cryopreserve porcine ovarian tissue and to confirm an occurrence of cryoinjuries. Briefly, cryoinjuries and apoptosis patterns in vitrified-warmed ovarian tissue were examined by histological evaluation and TUNEL assay respectively. In results, a damaged morphology of oocytes was detected among groups and the rate was significantly (p < 0.05) lower in vitrification group (25.8%) than freezing control group (67.7%), while fresh control group (6.6%) showed significantly (p < 0.05) lower than both groups. In addition, cryoinjury that form a wave pattern of tissues around follicles was found in the frozen control group, but not in the fresh control group as well as in the vitrification group. Apoptotic cells in follicle was observed only in freezing control group while no apoptotic cell was found in both fresh control and vitrification. Similarly, apoptotic patterns of tissues not in follicle were comparable between fresh control and vitrification groups while freezing control group showed increased tendency. Conclusively, it was confirmed that vitrification method has a prevention effect against cryoinjury and this method could be an alternative approach for cryopreservation of genetic material in pigs. Further study is needed to examine the viability of oocytes derived from vitrified-warmed ovarian tissue.

• 수산해양기술연구
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• 제59권2호
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• pp.145-154
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• 2023

In this study, to control the heading angle of a ship, which is constantly subjected to various internal and external disturbances during the voyage, an LADRC (linear active disturbance rejection control) design that focuses more on improving the disturbance removal performance was proposed. The speed rate of change of the ship's heading angle due to the turn of the rudder angle was selected as a significant factor, and the nonlinear model of the ship's maneuvering equation, including the steering gear, was treated as a total disturbance. It is the similar process with an LADRC design for the first-order transfer function model. At this time, the gains of the controller included in LADRC and the gains of the extended state observer were tuned to RCGAs (real-coded genetic algorithms) to minimize the integral time-weighted absolute error as an evaluation function. The simulation was performed by applying the proposed GA-LADRC controller to the heading angle control of the Mariner class vessel. In particular, it was confirmed that the proposed controller satisfactorily maintains and follows the set course even when the disturbances such as nonlinearity, modelling error, uncertainty and noise of the measurement sensor are considered.