• Journal of Institute of Control, Robotics and Systems
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• v.10 no.11
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• pp.1071-1076
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• 2004

It is a fuzzy controller that it is the most used method in the control of non-linear system. The most important part in the fuzzy controller is a design of fuzzy rules. Many algorithm that design fuzzy rules have proposed. And attention to the evolutionary computation is increasing in the recent days. Among them, the co-evolutionary algorithm is used in the design of optimal fuzzy rule. This paper takes advantage of a schema co-evolutionary algorithm. In order to verify the efficiency of the schema co-evolutionary algorithm, a fuzzy controller for the mobile robot control is designed by the schema co-evolutionary algorithm and it is compared with other parasitic co-evolutionary algorithm such as a virus-evolutionary genetic algorithm and a co-evolutionary method of Handa.

• The Plant Pathology Journal
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• v.35 no.5
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• pp.498-507
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• 2019

Odontoglossum ringspot virus (ORSV) is a member of the genus Tobamovirus. It is one of the most prevalent viruses infecting orchids worldwide. Earlier studies reported the genetic variability of ORSV isolates from Korea and China. However, the evolutionary rate, timescale, and phylogeographical analyses of ORSV were unclear. Twenty-one coat protein (CP) gene sequences of ORSV were determined in this study, and used them together with 145 CP sequences obtained from GenBank to infer the genetic diversities, evolutionary rate, timescale and migration of ORSV populations. Evolutionary rate of ORSV populations was $1.25{\times}10^{-3}nucleotides/site/y$. The most recent common ancestors came from 30 year ago (95% confidence intervals, 26-40). Based on CP gene, ORSV migrated from mainland China and South Korea to Taiwan island, Germany, Australia, Singapore, and Indonesia, and it also circulated within east Asia. Our study is the first attempt to evaluate the evolutionary rates, timescales and migration dynamics of ORSV.

• The Plant Pathology Journal
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• v.38 no.5
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• pp.533-540
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• 2022

Thunberg fritillary (Fritillaria thunbergii), a perennial used in traditional Chinese herbal medicine, is a members of the family Liliaceae. The degeneration of germplasm is a severe problem in the production of Fritillaria thunbergii var. chekiangensis. However, no information about viral infections of F. thunbergii var. chekiangensis has been reported. In this study, we sequenced the small RNAs of F. thunbergii var. chekiangensis from leaves and bulbs, and viruses were identified using a phylogenetic analysis and BLAST search for sequence. In addition, multiplex reverse transcriptase-polymerase chain reaction (RT-PCR) was used to rapidly detect viruses in this variety. Our study first reported that five viruses infected F. thunbergii var. chekiangensis. Among them, fritillary virus Y (FVY), lily mottle virus (LMoV), Thunberg fritillary mosaic virus (TFMV), and hop yellow virus (HYV) had been reported in F. thunbergii, while apple stem grooving virus was first reported in the genus Fritillaria. A multiplex RT-PCR method was developed to rapidly test the four viruses FVY, LMoV, TFMV, and HYV in F. thunbergii var. chekiangensis. Our results provide a better understanding of the infection of F. thunbergii var. chekiangensis by viruses and a basic reference for the better design of suitable control measures.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.365-370
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• 2001

The genetic algorithm that simulates the virus evolutionary theory has been developed applying to combinatorial optimization problems. The algorithm in this study uses only one individual and a population of viruses. The individual is attacked, inflected and improved by the viruses. The viruses are composed of flour genes (a pair of top gene and a pair of tail gene). If the individual is improved by the attacking, the inflection occurs. After the infection, the tail genes are mutated. If the same virus attacks several times and fails to inflect, the top genes of the virus are mutated. By this mutation, the individual can be improved effectively. In addition, the influence of the immunologic mechanism on evolution is simulated.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.679-682
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• 2003

In this paper, we propose a Genetic Algorithm (GA) using symbiotic evolutionary viruses. Our GA is based on both the building block hypothesis and the virus theory of evolution. The proposed GA aims to control a destruction of building blocks by discovering, keeping, and propagating of building blocks based on virus operation. Concretely, we prepare the group of individuals and the group of viruses. In our GA, the group of individuals searches solutions and the group of viruses searches building blocks. These searches done based on the symbiotic relation of both groups. Also, our GA has two types of virus evaluation techniques. One is that each virus is evaluated by the difference of the fitness of an individual between before and after infection of virus. Another is that all viruses aye evaluated by the difference of the fitness of an individual between before and after infection of all viruses. Furthermore, we applied the proposed GA to the minimum value search problem of a test function which has some local solutions far from the optimal solution. And, we discuss a difference of behaviors of the proposed GA based on each virus evaluation techniques.

• The Plant Pathology Journal
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• v.33 no.3
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• pp.296-306
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• 2017

Sugarcane mosaic virus (SCMV) is one of the most damaging viruses infecting sugarcane, maize and some other graminaceous species around the world. To investigate the genetic diversity of SCMV in Iran, the coat protein (CP) gene sequences of 23 SCMV isolates from different hosts were determined. The nucleotide sequence identity among Iranian isolates was more than 96%. They shared nucleotide identities of 75.5-99.9% with those of other SCMV isolates available in GenBank, the highest with the Egyptian isolate EGY7-1 (97.5-99.9%). The results of phylogenetic analysis suggested five divergent evolutionary lineages that did not completely reflect the geographical origin or host plant of the isolates. Population genetic analysis revealed greater between-group than within-group evolutionary divergence values, further supporting the results of the phylogenetic analysis. Our results indicated that natural selection might have contributed to the evolution of isolates belonging to the five identified SCMV groups, with infrequent genetic exchanges occurring between them. Phylogenetic analyses and the estimation of genetic distance indicated that Iranian isolates have low genetic diversity. No recombination was found in the CP cistron of Iranian isolates and the CP gene was under negative selection. These findings provide a comprehensive analysis of the population structure and driving forces for the evolution of SCMV with implications for global exchange of sugarcane germplasm. Gene flow, selection and somehow homologous recombination were found to be the important evolutionary factors shaping the genetic structure of SCMV populations.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.522-524
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• 1999

This paper addresses the systematic approach to the fuzzy modeling of the class of complex and uncertain nonlinear systems. While the conventional genetic algorithm (GA) only searches the global solution, Virus-Evolutionary Genetic Algorithm(VEGA) can search the global and local optimal solution simultaneously. In the proposed method the parameter and the structure of the fuzzy model are automatically identified at the same time by using VEGA. To show the effectiveness and the feasibility of the proposed method, a numerical example is provided. The performance of the proposed method is compared with that of conventional GA.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.3
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• pp.242-248
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• 2007

In this paper, we implement the internet-based remote control system for intelligent robot. For remote control of the robot, it uses the socket communication of the TCP/IP. It consists of the user interface and the robot control interface. Robot control interface transmits the navigation and environmental informations of the robot into the user interface. In order to transmit the large environmental images, a JPEG compression algorithm is used. User interface displays the navigation status of the robot and transmits the navigation order into the robot control interface. Also, we propose the design method of the fuzzy controller using navigation data acquired by expert's knowledge or experience. To do this, we use virus-evolutionary genetic algorithm(VEGA). Finally, we have shown the proposed system can be operated through the real world experimentations.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.325-327
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• 2007

In this paper, we implement the internet- based remote control system for intelligent robot. For remote control of the robot, it uses the socket communication of the TCP/IP. It consists of- the user interface and the robot control interface. Robot control interface transmits the navigation and environmental informations of the robot into the user interface. In order to transmit the large environmental images, a JPEG compression algorithm is used. User interface displays the navigation status of the robot and transmits the navigation order into the robot control interface. Also, we propose the design method of the fuzzy controller using navigation data acquired by expert's knowledge or experience. To do this, we use virus-evolutionary genetic algorithm(VEGA). Finally, we have shown the proposed system can be operated through the real world experimentations.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.08a
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• pp.90.1-90.1
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• 2013

Nature utilizes various of the colorization process. Some species of birds can express their mood of tempers by changing their collagen structures on skin. For example, turkey can change their skin color by expansion of the collagen structures, which are associated with the distinct color changes. Here, we developed bioinspired virus-based colorimetric sensors which can be genetically tuned for target molecule. Using M 13 bacteriophage, we fabricated responsive self-assembled color matrices composed of quasi-ordered fiber bundle structures. These virus matrices can exhibit color change by stimuli through fiber bundle structure modulation. Upon exposure of volatile organic compounds, the resulting multi-colored matrices exhibited distinct color changes with different ratios that can be recognized by the naked eyes. Using the directed evolutionary approaches, we genetically engineered the virus matrix to incorporate binding motif for explosive detection (i.e., trinitrotoluene (TNT)). Through utilizing a common handheld device (i.e., iPhone), we could distinguish TNT molecules down to 20 ppb in a selective manner. Our novel biomimetic virus colorimetric sensor can overcome current limitation for low response selectivity.