• Journal of Genetic Medicine
• /
• v.6 no.1
• /
• pp.38-55
• /
• 2009

Purpose: This study was undertaken to provide the framework for development of a genetic counseling training program, and an accreditation and certification process suitable for non-M.D. genetic counselors in Korea. Materials and Methods: Global standards of genetic counseling curriculums, training program accreditation (TPA), and the certification process for genetic counselors (CPGC) in the U.S.A and Japan were reviewed, and a questionnaire survey was performed to elicit opinions among health-care providers including physicians, nurses, technicians, researchers, and educators. In addition, input from professional communities, including the Korean Society of Medical Genetics (KSMG) and Institute for Genetic Testing Evaluation, was sought in formulating the framework of this study. Results: Comparison of U.S.A. and Japan educational systems showed similarities in curriculum, accreditation, and certification programs. Analysis of 117 respondents opinions showed a high level of agreement in the area of global standards; 88% indicated that KSMG should be in charge of TPA and CPGC, while 77% favored a certification exam composed of both written exam and interview components. Conclusion: Based upon this study we propose that the KSMG should be in charge of providing the TPA and CPGC for non-MD genetic counselors. Requirements for the entrance to a Master's degree genetic counseling program should be open to successful four year undergraduate students in all areas, provided the candidates demonstrate the abilities to master the graduate level of study in human genetics, clinical genetics, statistics, psychology, and other required subjects. Eligibility for certification should include qualified candidates of genetic counseling with no formally approved education, but a sufficient amount of clinical experience, in addition to accredited program graduates. Certification examinations should be carried out every two years and the certification should be good for five years, as is the case in Japan.

• Korean Journal of Agricultural Science
• /
• v.49 no.3
• /
• pp.431-440
• /
• 2022

Hanwoo cattle are a unique and historical breed in Korea that have been genetically improved and maintained by the national evaluation and selection system. The aim of this study was to provide information that can help improve the accuracy of the estimated breeding values in Hanwoo cattle by showing the difference between the imputation reference chip platforms of genomic data and the scaling factor of the genetic relationship matrix (GRM). In this study, nine sets of data were compared that consisted of 3 reference platforms each with 3 different scaling factors (-0.5, 0 and 0.5). The evaluation was performed using MTG2.0 with nine different GRMs for the same number of genotyped animals, pedigree, and phenotype data. A five multi-trait model was used for the evaluation in this study which is the same model used in the national evaluation system. Our results show that the Hanwoo custom v1 platform is the best option for all traits, providing a mean accuracy improvement by 0.1 - 0.3%. In the case of the scaling factor, regardless of the imputation chip platform, a setting of -1 resulted in a better accuracy increased by 0.5 to 1.6% compared to the other scaling factors. In conclusion, this study revealed that Hanwoo custom v1 used as the imputation reference chip platform and a scaling factor of -0.5 can improve the accuracy of the estimated breeding value in the Hanwoo population. This information could help to improve the current evaluation system.

• Journal of Electrical Engineering and Technology
• /
• v.10 no.1
• /
• pp.41-46
• /
• 2015

It is very important to make accurate forecast of wind power because of its indispensable requirement for power system stable operation. The research is to predict wind power by chaos and BP artificial neural networks (CBPANNs) method based on genetic algorithm, and to evaluate feasibility of the method of predicting wind power. A description of the method is performed. Firstly, a calculation of the largest Lyapunov exponent of the time series of wind power and a judgment of whether wind power has chaotic behavior are made. Secondly, phase space of the time series is reconstructed. Finally, the prediction model is constructed based on the best embedding dimension and best delay time to approximate the uncertain function by which the wind power is forecasted. And then an optimization of the weights and thresholds of the model is conducted by genetic algorithm (GA). And a simulation of the method and an evaluation of its effectiveness are performed. The results show that the proposed method has more accuracy than that of BP artificial neural networks (BP-ANNs).

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2008.04a
• /
• pp.416-421
• /
• 2008

A Metropolis genetic algorithm (MGA) is a newly-developed hybrid algorithm combining simple genetic algorithm (SGA) and simulated annealing (SA). In the algorithm, favorable features of Metropolis criterion of SA are incorporated in the reproduction operations of SGA. This way, MGA alleviates the disadvantages of finding imprecise solution in SGA and time-consuming computation in SA. It has been successfully applied and the efficiency has been verified for the practical structural design optimization. However, applicability of MGA for the wider range of problems should be rigorously proved through the solution of mathematical optimization problems. Thus, performances of MGA for the typical mathematical problems are investigated and compared with those of conventional algorithms such as SGA, micro genetic algorithm (${\mu}GA$), and SA. And, for better application of MGA, the effects of acceptance level are also presented. From numerical Study, it is again verified that MGA is more efficient and robust than SA, SGA and ${\mu}GA$ in the solution of mathematical optimization problems having various features.

• Development and Reproduction
• /
• v.21 no.3
• /
• pp.229-235
• /
• 2017

In the field of reproductive medicine, assessment of sperm motility is a key factor for achieving successful artificial insemination, in vitro fertilization, or intracellular sperm injection. In this study, the motility of boar sperms was estimated using real-time imaging via confocal microscopy. To confirm this confocal imaging method, flagellar beats and whiplash-like movement angles were compared between fresh and low-temperature-preserved ($17^{\circ}C$ for 24 h) porcine sperms. Low-temperature preservation reduced the number of flagellar beats from $11.0{\pm}2.3beats/s$ (fresh sperm) to $5.7{\pm}1.8beats/s$ and increased the flagellar bending angle from $19.8^{\circ}{\pm}13.8^{\circ}$ (fresh) to $30.6^{\circ}{\pm}15.6^{\circ}$. These data suggest that sperm activity can be assessed using confocal microscopy. The observed motility patterns could be used to develop a sperm evaluation index and automated confocal microscopic sperm motility analysis techniques.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.7 no.11
• /
• pp.2702-2719
• /
• 2013

A new optimal scheme based on curvelet transform is proposed for retinal image enhancement (RIE) using real-coded quantum genetic algorithm. Curvelet transform has better performance in representing edges than classical wavelet transform for its anisotropy and directional decomposition capabilities. For more precise reconstruction and better visualization, curvelet coefficients in corresponding subbands are modified by using a nonlinear enhancement mapping function. An automatic method is presented for selecting optimal parameter settings of the nonlinear mapping function via quantum genetic search strategy. The performance measures used in this paper provide some quantitative comparison among different RIE methods. The proposed method is tested on the DRIVE and STARE retinal databases and compared with some popular image enhancement methods. The experimental results demonstrate that proposed method can provide superior enhanced retinal image in terms of several image quantitative evaluation indexes.

• Journal of Satellite, Information and Communications
• /
• v.6 no.1
• /
• pp.6-11
• /
• 2011

In this paper presents a new approach to evaluate reliability indices of electric distribution systems using genetic Algorithm (GA). The use of reliability evaluation is an important aspect of distribution system planning and operation to adjust the reliability level of each area. In this paper, the reliability model is based on the optimal load transferring problem to minimize load generated load point outage in each sub-section. This approach is one of the most difficult procedures and become combination problems. A new approach using GA was developed for this problem. GA is a general purpose optimization technique based on principles inspired from the biological evolution using metaphors of mechanisms such as natural selection, genetic recombination and survival of the fittest. Test results for the model system with 24 nodes 29 branches are reported in the paper.

• Journal of Electrical Engineering and Technology
• /
• v.9 no.6
• /
• pp.2042-2048
• /
• 2014

In medium voltage electrical distribution networks, reforming the loss reduction is important, and in line with this, the issue of system engineering and use of proper equipment Expansion of distribution systems results in higher system losses and poor voltage regulation. Therefore, an efficient and effective distribution system has become more important. So, proper selection of conductors in the distribution system is crucial as it determines the current density and the resistance of the line. Evaluation of aging conductors for losses and costs imposed in addition to the careful planning of technical and economic networks can be identified in the network design. In this paper the use of imperialist competitive algorithm; genetic algorithm; is proposed to optimal branch conductor selection and reconstruction in radial distribution systems planning. The objective is to minimize the overall cost of annual energy losses and depreciation on the cost of conductors to improve productivity given the maximum current carrying capacity and acceptable voltage levels. Simulations are carried out on 69-bus radial distribution network using genetic algorithm approaches to show the accuracy as well as the efficiency of the proposed solution technique.

• Asian-Australasian Journal of Animal Sciences
• /
• v.25 no.1
• /
• pp.22-27
• /
• 2012

The experiment involved observations of 2,514 Holstein-Friesian cows to determine the effects of environmental factors (cow's age, calving season, weight and sex of calves, housing system) and genetic factors on gestation length in dairy cattle and the correlation between gestation length and other reproductive traits (calving ease, stillbirth rates and placental expulsion). Genetic parameters were estimated based on the sires of calved cows (indirect effect) and the sires of live-born calves (direct effect). The following factors were found to contribute to prolonged gestation: increasing cow's age, male fetuses and growing fetus weight. Optimal gestation length was determined in the range of 275-277 days based on calving ease and stillbirth rates. The heritability of gestation length was estimated at 0.201-0.210 by the direct effect and 0.055-0.073 by the indirect effect. The resulting genetic correlations suggest that the efforts to optimize (prolong) gestation length could exert an adverse influence on the breeding value of bulls by increasing perinatal mortality and calving difficulty. The standard errors of the investigated parameters were relatively high, suggesting that any attempts to modify gestation length for the purpose of improving calving ease and reducing stillbirth rates should be introduced with great caution.

• Journal of Korea Multimedia Society
• /
• v.3 no.5
• /
• pp.470-478
• /
• 2000

Color images from various application areas have their own characteristics. Practical segmentation systems need specialized methods to death with the characteristics. In this paper. we propose a distributed genetic algorithm based segmentation method for color breast carcinoma cell images. To extract positive nuclei and negative nuclei from the cell images, a distributed genetic algorithm with improved genetic operations and an evaluation function is used. As initial values, representative colors from images are introduced to work well with the cell images. A test to verify the validity of the proposed method shows well-segmented images. This result suggests that the method is pertinent to be but into practical use for the images haying limited objects with limited colors.