• Asian-Australasian Journal of Animal Sciences
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• v.17 no.2
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• pp.153-158
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• 2004

Data containing 14,188 lactation and reproductive records of Korean Holstein cows at first parity distributed across 3,734 herd-year-season groups were analyzed to get genetic (co)variance estimates for milk yield, fat yield, calving ease, and days open. Milk and Fat yields were adjusted to 305 d. Heritabilities and genetic correlations were estimated in two different animal models on which were included direct genetic effects (Model 1) and direct+maternal genetic effects (Model 2) using REML algorithms. Milk and fat yields were affected by age at first calving as linear and quadratic. Heritability estimates of direct effects were 0.25 for milk yield, 0.17 for fat yield, 0.03 for calving ease and 0.03 for days open in Model 2. These estimates for maternal effects were 0.05, 0.08, 0.04 and less than 0.01 for each corresponding trait. Milk productions at first lactation were to show genetically favorable correlation with calving ease and days open for direct genetic effects (-0.24 - -0.11). Moreover, calving ease was correlated with days open of 0.30 for direct genetic effects. Correlations between direct and maternal effects for each trait were negatively correlated (-0.63 - -0.32). This study suggested that maternal additive genetic variance would be not ignorable for genetic evaluation of milk production as well as reproductive traits such as calving ease and days open at first parity. Furthermore, difficult calving would genetically influence the next conception.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.167-174
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• 2022

In metaheuristic algorithms such as Genetic Algorithm (GA), initial population has a significant impact as it affects the time such algorithm takes to obtain an optimal solution to the given problem. In addition, it may influence the quality of the solution obtained. In the machine learning field, feature selection is an important process to attaining a good performance model; Genetic algorithm has been utilized for this purpose by scientists. However, the characteristics of Genetic algorithm, namely random initial population generation from a vector of feature elements, may influence solution and execution time. In this paper, the use of a statistical algorithm has been introduced (Chi2) for feature relevant checks where p-values of conditional independence were considered. Features with low p-values were discarded and subject relevant subset of features to Genetic Algorithm. This is to gain a level of certainty of the fitness of features randomly selected. An ensembled-based learning model for Hepatitis has been developed for Hepatitis C stage classification. 1385 samples were used using Egyptian-dataset obtained from UCI repository. The comparative evaluation confirms decreased in execution time and an increase in model performance accuracy from 56% to 63%.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.563-570
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• 2004

Genetic algorithms have been successfully applied to various optimization problems belonging to NP-hard problems. The sequential ordering problems(SOP) and the job shop scheduling problems(JSP) are well-known NP-hard problems with strong influence on industrial applications. Both problems share some common properties in that they have some imposed precedence constraints. When genetic algorithms are applied to this kind of problems, it is desirable for genetic operators to be designed to produce chromosomes satisfying the imposed precedence constraints. Several genetic operators applicable to such problems have been proposed. We call such genetic operators precedence-preserving genetic operators. This paper presents three existing precedence-preserving genetic operators: Precedence -Preserving Crossover(PPX), Precedence-preserving Order-based Crossover (POX), and Maximum Partial Order! Arbitrary Insertion (MPO/AI). In addition, it proposes two new operators named Precedence-Preserving Edge Recombination (PPER) and Multiple Selection Precedence-preserving Order-based Crossover (MSPOX) applicable to such problems. It compares the performance of these genetic operators for SOP and JSP in the perspective of their solution quality and execution time.

• Journal of Ecology and Environment
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• v.43 no.4
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• pp.454-461
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• 2019

Background: Ikonnikov's whiskered bat (Myotis ikonnikovi) is found throughout the Korean Peninsula, as well as in Kazakhstan, Russia, Mongolia, China, and Japan. It is small-sized and primarily inhabits old-growth forests. The decrease and fragmentation of habitats due to increased human activity may influence the genetic structure of bat populations. This study was designed to elucidate the population genetic structure of M. ikonnikovi using mitochondrial genes (cytochrome oxidase I and cytochrome b). Results: The results showed that M. ikonnikovi populations from Korea have high genetic diversity. Although genetic differentiation was not detected for the COI gene, strong genetic differentiation of the Cytb gene between Mt. Jeombong and Mt. Jiri populations was observed. Moreover, the results indicated that the gene flow of the maternal lineage may be limited. Conclusions: This study is the first to identify the genetic population structure of M. ikonnikovi. We suggest that conservation of local populations is important for sustaining the genetic diversity of the bat, and comprehensive studies on factors causing habitat fragmentation are required.

• Communications for Statistical Applications and Methods
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• v.12 no.3
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• pp.759-771
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• 2005

Twin studies are one of the most widely used methods for quantifying the influence of genetic and environmental factors on some traits such as a life span or a disease. In this paper we propose a genetic mixed linear model for twin survival time data, which allows us to separate the genetic component from the environmental component. Inferences are based upon the hierarchical likelihood (h-likelihood), which provides a statistically efficient and simple unified framework for various random-effect models. We also propose a simple and fast computation method for analyzing a large data set on twin survival study. The new method is illustrated to the survival data in Swedish Twin Registry. A simulation study is carried out to evaluate the performance.

• Industrial Engineering and Management Systems
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• v.8 no.4
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• pp.228-238
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• 2009

This paper first presents two supply chain design problems: 1) a factory location setting and factory selection problem, and 2) a factory location setting and factory/supplier selection problem. The first involves a number of location known retailers choosing one factory to supply their demands from a number of factories whose locations are to be determined. The goal is to minimize the transportation and manufacturing cost to satisfy the demands. The problem is then augmented into the second problem, where the procurement cost of the raw materials from a chosen material supplier (from a number of suppliers) is considered for each factory. Economic beneficial is taken into account in the cost evaluation. Therefore, the partner selections will influence the cost of the supply chain significantly. To solve these problems, an agent gaming and genetic algorithm hybrid method (AGGAHM) is proposed. The AGGAHM consecutively and alternatively enable and disable the advancement of agent gaming and the evolution of genetic computation. Computation results on solving a number of examples by the AGGAHM were compared with those from methods of a general genetic algorithm and a mutual frozen genetic algorithm. Results showed that the AGGAHM outperforms the methods solely using genetic algorithms. In addition, various parameter settings are tested and discussed to facilitate the supply chain designs.

• Proceedings of the Korean Society of Applied Pharmacology
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• 2006.11a
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• pp.13-19
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• 2006

• 한국약용작물학회:학술대회논문집
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• 2006.11a
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• pp.13-19
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• 2006

• Journal of Science and Technology Studies
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• v.14 no.1
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• pp.59-85
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• 2014

This study aims to highlight the social aspects of genetic discrimination as another shadow that biotechnology can influence on social life. To do so, the definition of "genetic discrimination" and three perspectives (exceptionalism, expressivism, and human right discourse) were reviewed. In addition, the Genetic Information Nondiscrimination Act (GINA) of the United States and the Bioethics and Safety Act of Korea were analyzed. Several social implications for establishing the research and policies of genetic discrimination based on the existing research results of perceived genetic discrimination (the experiences, fears, and coping strategies of genetic discrimination) were suggested. These included public consensus on the definition of genetic discrimination and emphasis on a human rights approach against genetic discrimination; concerns regarding genetic discrimination in both the personal and public domains; raising the consciousness of both health care providers and the public regarding genetic discrimination; and developing psycho-social coping strategies for decreasing the fear of discrimination of asymptomatic people (hereditary carriers).

• Wind and Structures
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• v.11 no.6
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• pp.497-512
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• 2008

In this paper, optimum methods of wind-induced vibration control of high-rise buildings are mainly studied. Two optimum methods, genetic algorithms (GA) method and Rayleigh damping method, are firstly employed and proposed to perform optimum study on wind-induced vibration control, six target functions are presented in GA method based on spectrum analysis. Structural optimum analysis programs are developed based on Matlab software to calculate wind-induced structural responses. A high-rise steel building with 20-storey is adopted and 22 kinds of control plans are employed to perform comparison analysis to validate the feasibility and validity of the optimum methods considered. The results show that the distributions of damping coefficients along structural height for mass proportional damping (MPD) systems and stiffness proportional damping (SPD) systems are entirely opposite. Damping systems of MPD and GAMPD (genetic algorithms and mass proportional damping) have the best performance of reducing structural wind-induced vibration response and are superior to other damping systems. Standard deviations of structural responses are influenced greatly by different target functions and the influence is increasing slightly when higher modes are considered, as shown fully in section 5. Therefore, the influence of higher modes should be considered when strict requirement of wind-induced vibration comfort is needed for some special structures.