• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.721-726
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• 2020

Genetic algorithm was first introduced to study adaption phenomena occurring in nature based on Darwin's theory of survival of the fittest. It has been used when analytical approach is not possible because of a large number of variables. In this paper, we demonstrated that genetic algorithm could be used to obtain physically optimized experimental values. We programmed a genetic algorithm that uses a few Gaussian functions to find a given function value and the same algorithm was connected to the laser system to obtain laser pulses of 40fs of maximum pulse width and 1mJ of maximum output power. This study shows that genetic algorithm can be applied to laser systems to obtain the optimized laser pulses.

• Development and Reproduction
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• v.24 no.3
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• pp.241-248
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• 2020

This study used a PCR-based genetic analysis platform to create a hierarchical polar dendrogram of Euclidean genetic distances for two salmonid species, Oncorhynchus mykiss (rainbow trout, RT) and Oncorhynchus masou (masu salmon, MS). The species were distantly related to other fish species based on PCR results from using the designed oligonucleotide primer series. Five oligonucleotide primers were used to generate 330 and 234 scorable fragments in the RT and MS populations, respectively. The DNA fragments ranged in size from approximately 50 bp to more than 2,000 bp. The bandsharing (BS) results showed that the RT population had a higher average BS value (0.852) than that for the MS population (0.704). The genetic distance between individuals supported the presence of adjacent affiliation in cluster I (RT 01-RT 11). The observation of a significant genetic distance between the two Oncorhynchus species verifies that this PCR-based technique can be a useful approach for individual- and population-based biological DNA investigations. The results of this type of investigation can be useful for species safekeeping and the maintenance of salmonid populations in the mountain streams of Korea.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.283-286
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• 2007

This paper proposes a genetic algorithm (GA) approach to instance selection in case-based reasoning (CBR) for the prediction of Korea Stock Price Index (KOSPI). CBR has been widely used in various areas because of its convenience and strength in complex problem solving. Nonetheless, compared to other machine learning techniques, CBR has been criticized because of its low prediction accuracy. Generally, in order to obtain successful results from CBR, effective retrieval of useful prior cases for the given problem is essential. However, designing a good matching and retrieval mechanism for CBR systems is still a controversial research issue. In this paper, the GA optimizes simultaneously feature weights and a selection task for relevant instances for achieving good matching and retrieval in a CBR system. This study applies the proposed model to stock market analysis. Experimental results show that the GA approach is a promising method for instance selection in CBR.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.2
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• pp.60-68
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• 1992

Fuzzy logic rule based controller has many desirable advantages, whih are simple to implement on the real time and need not the information of structure and dynamic characteristics of the system. Thus, nowadays, the scope of the application of the fuzzy logic controller becomes enlarged. But, if the controlled plant is a time-varying/nonlinear system, it is not easy to construct the fuzzy logic rules which need the knowledge of and expert. In this paper, an approach by which the logic control rules can be auto-generated using the genetic algorithm that is known to be very effective in the optimization problem will be proposed and the effectiveness of the proposed approach will be verified by computer simulation of the 2 d.o.f. planner robot.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.4
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• pp.91-99
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• 1996

A hybrid approach employing both the genetic algorithm and the newton-raphson method is proposed for the electrical impedance computed tomography (EICT) image reconstruction. Computational experiments based on the new concept have shown promising results for several noise-free models. In particular, the resistance distribution of the tested models having resistivity ratio up to 100:1 has been reconstructed sucessfully. Using the proposed mehtod, it is also possible to get the reconstruction by the conventional iterative approaches be difficult to vonverge to a robust solution. If the compution power is enhanced further, the proposed method is expected to stimulate the practical applications of the EICT technology in the near future.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.7-11
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• 2004

This paper proposes a new immunotronic approach for the fault detection in hardware. The suggested method is, inspired by biology and its implementation is based on genetic algorithm. Tolerance conditions in the immunotronic system for fault detection correspond to the antibodies in the biological immune system. A novel algorithm of generating tolerance conditions is suggested based on the principle of the antibody diversity and GA optimization is employed to select mature tolerance conditions in immunotronic fault detection system. The suggested method is applied to the fault detection for MCNC benchmark FSMs (finite state machines) and its effectiveness is demonstrated by the computer simulation.

• BMB Reports
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• v.37 no.1
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• pp.53-58
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• 2004

With advances in determining the entire DNA sequence of the human genome, it is now critical to systematically identify the function of a number of genes in the human genome. These biological challenges, especially those in human diseases, should be addressed in human cells in which conventional (e.g. genetic) approaches have been extremely difficult to implement. To overcome this, several approaches have been initiated. This review will focus on the development of a novel 'chemical genetic/genomic approach' that uses small molecules to 'probe and identify' the function of genes in specific biological processes or pathways in human cells. Due to the close relationship of small molecules with drugs, these systematic and integrative studies will lead to the 'medicinal systems biology approach' which is critical to 'formulate and modulate' complex biological (disease) networks by small molecules (drugs) in human bio-systems.

• Structural Engineering and Mechanics
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• v.56 no.1
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• pp.107-121
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• 2015

The main objective of this research is to present the procedures of combining topology, shape & sizing optimization for truss structure by employing strain energy as objective function under the constraints of volume fractions which yield more general solution than that of total weight approach. Genetic Algorithm (GA) is used as searching engine for the convergence solution. A number of algorithms from previous research are used for evaluating the feasibility and stability of candidate to accelerate convergence and reduce the computational effort. It is followed by solving problem for topology & shape optimization and topology, shape & sizing optimization of truss structure to illustrate the feasibility of applying the objective function of strain energy throughout optimization stages.

• Structural Engineering and Mechanics
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• v.43 no.6
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• pp.795-821
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• 2012

The size and topology of geometrically nonlinear dome structures are optimized thereby minimizing both its entire weight & joint (node) displacements and maximizing load-carrying capacity. Design constraints are implemented from provisions of American Petroleum Institute specification (API RP2A-LRFD). In accordance with the proposed design constraints, the member responses computed by use of arc-length technique as a nonlinear structural analysis method are checked at each load increment. Thus, a penalization process utilized for inclusion of unfeasible designations to genetic search is correspondingly neglected. In order to solve this complex design optimization problem with multiple objective functions, Non-dominated Sorting Genetic Algorithm II (NSGA II) approach is employed as a multi-objective optimization tool. Furthermore, the flexibility of proposed optimization is enhanced thereby integrating an automatic dome generating tool. Thus, it is possible to generate three distinct sphere-shaped dome configurations with varying topologies. It is demonstrated that the inclusion of brace (diagonal) members into the geometrical configuration of dome structure provides a weight-saving dome designation with higher load-carrying capacity. The proposed optimization approach is recommended for the design optimization of geometrically nonlinear dome structures.

• Archives of Pharmacal Research
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• v.26 no.3
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• pp.183-191
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• 2003

Nucleic acid therapies represent a direct genetic approach for cancer treatment. Such an approach takes advantage of mechanisms that activate genes known to confer a growth advantage to neoplastic cells. The ability to block the expression of these genes allows exploration of normal growth regulation. Progress in antisense technology has been rapid, and the traditional antisense inhibition of gene expression is now viewed on a genomic scale. This global view has led to a new vision in antisense technology, the elimination of nonspecific and undesirable side effects, and ultimately, the generation of more effective and less toxic nucleic acid medicines. Several antisense oligonucleotides are in clinical trials, are well tolerated, and are potentially active therapeutically. Antisense oligonucleotides are promising molecular medicines for treating human cancer in the near future.