• Asian Oncology Nursing
• /
• v.12 no.4
• /
• pp.267-273
• /
• 2012

Purpose: The purpose of this review article is to introduce how the Korean Society of Genetic Nursing (KSGN) has evolved and tried to translate genomic knowledge to nursing practice, and then to suggest the future role of genetic nurses in Korea. Methods: A literature review was performed and the current status of genetic counselling in Korea was explored. Then the educational and clinical experiences of the authors were incorporated. Finally, the main activities of Korean nursing for genetics were identified. Results: Two types of genetic counsellor certification have been issued in Korea: one is issued by the Korean Society of Genetic Medicine, another by the Korean Society of Breast Cancer since June 2011. A few Korean nursing researchers have continuously performed research related to genetic nursing and undertook several research projects funded by the government since 2003. In February 2011, KSGN was established and is now trying to establish further international networks. Conclusion: Nursing genetic experts should be trained to integrate all specialties for genetic counselling, so they can provide holistic genetic services including ethical, legal, and social issues (ELSI).

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.06a
• /
• pp.646-651
• /
• 1998

Fuzzy control has been used successfully in many practical applications. In traditional methods, experience and control knowledge of human experts are needed to design fuzzy controllers. However, it takes much time and cost. In this paper, an automatic design method for fuzzy controllers using genetic algorithms is proposed. In the method, we proposed an effective encoding scheme and new genetic operators. The maximum number of linguistic terms is restricted to reduce the number of combinatorial fuzzy rules in the research space. The proposed genetic operators maintain the correspondency between membership functions and control rules. The proposed method is applied to a cart centering problem. The result of the experiment has been satisfactory compared with other design methods using genetic algorithms.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.956-959
• /
• 1996

In this study, we propose a neuro-genetic controller combined with a linear controller in parallel to improve the tracking performance of the Line of Sight(LOS) stabilization system and reject the effect of disturbances. A Genetic Algorithm(GA) is used to optimize weights of the neuro-genetic controller since this algorithm can search a global minimum without derivatives or other auxiliary knowledge. The LOS system is very complex and has limited measurable output data. Under these specific circumstances GA solves many problems that other training methods have. Computer simulation results show that the, proposed controller makes better tracking response and rejection of disturbance than a linear controller.

• Asian-Australasian Journal of Animal Sciences
• /
• v.18 no.12
• /
• pp.1696-1700
• /
• 2005

Five China native cattle breeds have been characterized by using 10 microsatellite DNA markers. The studied populations can be divided into five groups: Luxi cattle, Nanyang cattle, Jinnan cattle, Qinchuan cattle and Yanbian cattle. Allele frequencies were calculated and used for the characterization of the breeds and the study of their genetic relationships. Heterozygosity, polymorphism information content, the effective number of alleles was calculated. Nei' standard genetic distance (1978) was calculated and used for a neighbor-joining tree construction. NJ tree showed that Luxi cattle, Nanyang cattle, Jinnan cattle and Qinchuan cattle are closely related, whereas Yanbian cattle are clearly distinct from other four populations. The genetic relationship of five breeds corresponds to their history and geographic origins. This work analyzes the recent origin of these populations and contributes to the knowledge and genetic characterization of China native breeds.

• Journal of Institute of Control, Robotics and Systems
• /
• v.4 no.5
• /
• pp.624-629
• /
• 1998

Evolutionary computation techniques can solve search problems using simulated evolution based on the ‘survival of the fittest’. Recently, the genetic programming (GP) which evolves computer programs using the genetic algorithm was introduced. In this paper, the genetic programming technique is used in order to design a rule based controller consisting of condition-action rules for an unknown system. No a priori knowledge about the structure of the controller is needed. Representation of a solution, functions and terminals in GP are analyzed, and a method of constructing a fuzzy logic controller using the obtained rule based controller is described. A simulation example using a nonlinear system shows the validity and efficiency of the proposed method.

• Proceedings of the Korean Society of Fisheries Technology Conference
• /
• 2003.05a
• /
• pp.229-230
• /
• 2003

Shortnecked clam is a commercially important mollusks species, which is distributed all over the Yellow Sea. Consequent of the rapid increase in seed production, there is a need to understand the genetic composition of wild shortnecked clam populations in order to evaluate exactly the latent genetic effects induced by seed production operations. Many genetic and molecular researches were made because RAPD-PCR is a simple and rapid method for determining genetic diversity and similarity in various organisms with the advantage that no prior knowledge of the genome under research is needed (Fischer et at., 2000). (omitted)

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1996.10a
• /
• pp.27-34
• /
• 1996

GENIE is a learning-based engine for building intelligent systems. Learning in GENIE proceeds by incrementally modeling its human or technical environment using a neural network and a genetic algorithm. The neural network is used to represent the knowledge for solving a given task and has the ability to grow its structure. The genetic algorithm provides the neural network with training examples by actively exploring the example space of the problem. Integrated into the training examples by actively exploring the example space of the problem. Integrated into the GENIE system architecture, the genetic algorithm and the neural network build a virtually self-teaching autonomous learning system. This paper describes the structure of GENIE and its learning components. The performance is demonstrated on a robot learning problem. We also discuss the lessons learned from experiments with GENIE and point out further possibilities of effectively hybridizing genetic algorithms with neural networks and other softcomputing techniques.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.67 no.6
• /
• pp.767-772
• /
• 2018

Recently, some meta-heuristic algorithms, such as GA(Genetic Algorithm) and GP(Genetic Programming), have been used to optimize CNN(Convolutional Neural Network). The CNN, which is one of the deep learning models, has seen much success in a variety of computer vision tasks. However, designing CNN architectures still requires expert knowledge and a lot of trial and error. In this paper, the recent attempts to automatically construct CNN architectures are investigated and analyzed. First, two GA based methods are summarized. One is the optimization of CNN structures with the number and size of filters, connection between consecutive layers, and activation functions of each layer. The other is an new encoding method to represent complex convolutional layers in a fixed-length binary string, Second, CGP(Cartesian Genetic Programming) based method is surveyed for CNN structure optimization with highly functional modules, such as convolutional blocks and tensor concatenation, as the node functions in CGP. The comparison for three approaches is analysed and the outlook for the potential next steps is suggested.

• Journal of Genetic Medicine
• /
• v.19 no.2
• /
• pp.57-62
• /
• 2022

Systemic autoinflammatory diseases (SAIDs) are characterized by unprovoked inflammatory episodes such as recurrent/periodic fever, serositis, skin lesions, abdominal symptoms, arthritis/arthralgia, and central nervous system involvement. Genetic diagnosis of SAIDs has been challenging because disease manifestations overlap among themselves and with other immunological disease categories, such as infection and autoimmune diseases. However, the advent of next-generation sequencing (NGS) technologies and expanding knowledge about the innate immunity and inflammation have made the routine genetic diagnosis of SAIDs possible. Here, we review the recurrent/periodic fevers, other recently identified autoinflammatory diseases, and type I interferonopathies, and discuss the clinical usefulness of NGS targeted sequencing for SAIDs, and recent advance of understandings for this heterogeneous disease group as for underlying primary immunodeficiency.

• Childhood Kidney Diseases
• /
• v.27 no.1
• /
• pp.11-18
• /
• 2023

Remarkable advances in genetic diagnosis expanded our knowledge about inherited tubulopathies and other genetic kidney diseases. This review suggests a simple categorization of inherited tubular disease, clarifies the concept of autosomal dominant tubulointerstitial kidney disease (ADTKD), and introduces novel therapies developed for tubulopathies. Facing patients with suspicious tubular disorders, clinicians should first evaluate the status of volume and acid-base. This step helps the clinicians to localize the affected segment and to confirm genetic diagnosis. ADTKD is a recently characterized disease entity involving tubules. The known causative genes are UMOD, MUC1, REN, and HNF1β. Still, only half of ADTKD patients show mutations for these four identified genes. Whole exome sequencing is a suitable diagnostic tool for tubulopathies, especially for ADTKD. Genetic approaches to treat tubulopathies have progressed recently. Despite the practical obstacles, novel therapies targeting inherited tubulopathies are currently in development.