• Interdisciplinary Bio Central
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• v.3 no.4
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• pp.15.1-15.11
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• 2011

Background: Histone deacetylase (HDAC) 8 is one of its family members catalyzes the removal of acetyl groups from N-terminal lysine residues of histone proteins thereby restricts transcription factors from being expressed. Inhibition of HDAC8 has become an emerging and effective anti-cancer therapy for various cancers. Application computational methodologies may result in identifying the key components that can be used in developing future potent HDAC8 inhibitors. Results: Facilitating the discovery of novel and potential chemical scaffolds as starting points in the future HDAC8 inhibitor design, quantitative structure-activity relationship models were generated with 30 training set compounds using genetic function approximation (GFA) and Bayesian algorithms. Six GFA models were selected based on the significant statistical parameters calculated during model development. A Bayesian model using fingerprints was developed with a receiver operating characteristic curve cross-validation value of 0.902. An external test set of 54 diverse compounds was used in validating the models. Conclusions: Finally two out of six models based on their predictive ability over the test set compounds were selected as final GFA models. The Bayesian model has displayed a high classifying ability with the same test set compounds and the positively and negatively contributing molecular fingerprints were also unveiled by the model. The effectively contributing physicochemical properties and molecular fingerprints from a set of known HDAC8 inhibitors were identified and can be used in designing future HDAC8 inhibitors.

• Journal of the Korean Society of Propulsion Engineers
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• v.8 no.3
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• pp.44-52
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• 2004

In this study, a component map generation method using experimental data and the genetic algorithms are newly proposed. In order to generate the performance map for components of this engine, after obtaining engine performance data through many experimental tests, and then the third order equations which have relationships the mass flow function the pressure ratio and the isentropic efficiency as to the engine rotational speed were derived by using the genetic algorithms. A steady-state performance analysis was performed with the generated maps of the compressor by the commercial gas turbine performance analysis program GASTURB. In comparison, it was found that the component maps can be generated from the experimental test data by using the genetic algorithms, and it was confirmed that the analysis results using the generated maps were very similar to those using the scaled maps from the GASTURB.

• Journal of KSNVE
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• v.11 no.1
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• pp.147-155
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• 2001

This paper is concerned with the real-time automatic tuning of the multi-input multi-output positive position feedback controllers for smart structures by the genetic algorithms. The genetic algorithms have proven its effectiveness in searching optimal design parameters without falling into local minimums thus rendering globally optimal solutions. The previous real-time algorithm that tunes a single control parameter is extended to tune more parameters of the MIMO PPF controller. We employ the MIMO PPF controller since it can enhance the damping value of a target mode without affecting other modes if tuned properly. Hence, the traditional positive position feedback controller can be used in adaptive fashion in real time. The final form of the MIMO PPF controller results in the centralized control, thus it involves many parameters. The bounds of the control Parameters are estimated from the theoretical model to guarantee the stability. As in the previous research, the digital MIMO PPF control law is downloaded to the DSP chip and a main program, which runs genetic algorithms in real time, updates the parameters of the controller in real time. The experimental frequency response results show that the MIMO PPF controller tuned by GA gives better performance than the theoretically designed PPF. The time response also shows that the GA tuned MIMO PPF controller can suppress vibrations very well.

• Structural Engineering and Mechanics
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• v.23 no.4
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• pp.387-407
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• 2006

A Genetic Algorithm (hereinafter GA) based optimum design algorithm and program for plane steel frames with partially restrained connections is presented. The algorithm was incorporated with the refined plastic hinge analysis method, in which geometric nonlinearity was considered by using the stability functions of beam-column members and material nonlinearity was considered by using the gradual stiffness degradation model that included the effects of residual stress, moment redistribution by the occurrence of plastic hinges, partially restrained connections, and the geometric imperfection of members. In the genetic algorithm, a tournament selection method and micro-GAs were employed. The fitness function for the genetic algorithm was expressed as an unconstrained function composed of objective and penalty functions. The objective and penalty functions were expressed, respectively, as the weight of steel frames and the constraint functions which account for the requirements of load-carrying capacity, serviceability, ductility, and construction workability. To verify the appropriateness of the present method, the optimum design results of two plane steel frames with fully and partially restrained connections were compared.

• Asian Oncology Nursing
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• v.11 no.3
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• pp.200-209
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• 2011

Purpose: The purpose of this micro-ethnography is to examine whether science and societal changes impact family communication patterns among a convenience sample of 16 Korean women. Methods: The authors observed family communication in the context of a new breast cancer genetic screening and diagnostic testing program to detect BRCA gene mutations in Korean women at highest risk. Results: Analysis of in-depth interviews and field notes taken during participant observation illustrated that communication patterns in families vary according to a woman's position in the family. If a grandmother tests positive for a gene mutation, her daughters make decisions on her behalf; they open and maintain the communication channel among family members. If a housewife is diagnosed with cancer and a genetic mutation, she immediately consults her husband and her sisters. The husband creates an open communication channel between his wife, his parents and his siblings. As a result, a woman's cancer is a concern for the whole family not merely a woman's secret or crisis. Conclusion: Cultural differences are important to consider when designing new genetic service programs in different countries.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1322-1327
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• 2003

It is important to determine supporting locations for structural stability of a structure under non-uniform load in space interfered by other parts. In this case, There are many local optima with discontinuous design space. Therefore, The traditional optimization methods based on derivative are not suitable. Whereas, Genetic algorithm(GA) based on stochastic search technique is a very robust and general method. This paper has been presented to determine supporting locations of the vertical supports for reducing stress of the KSTAR(Korea super Superconducting Tokamak Advanced Research) IVCC(In-vessel control coil) under non-uniform electromagnetic load and space interfered by other parts using genetic algorithm. For this study, we develop a program combining finite element analysis with a genetic algorithm to perform structural analysis of IVCC. In addition, this paper presents a technique to perform optimization with FEM when design variables are trapped in an incongruent design space.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.7 s.184
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• pp.84-92
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• 2006

This paper deals with determination of motions of a humanoid robot using genetic algorithm. A humanoid robot has some problems of the structural instability basically. So, we have to consider the stable walking gait in gait planning. Besides, it is important to make the smoothly optimal gait for saving the electric power. A mobile robot has battery to move autonomously. But a humanoid robot needs more electric power in order to drive many joints. So, if movements of walking joint don't maintain optimally, it is hard to sustain the battery power during the working period. Also, if a gait trajectory doesn't have optimal state, the expected lift span of joints tends to be decreased. Also, if a gait trajectory doesn't have optimal state, the expected lift span of joints tends to be decreased. To solve these problems, the genetic algorithm is employed to guarantee the optimal gait trajectory. The fitness functions in a genetic algorithm are introduced to find out optimal trajectory, which enables the robot to have the less reduced jerk of joints and get smooth movement. With these all process accomplished by PC-based program, the optimal solution could be obtained from the simulation. In addition, we discuss the design consideration fur the joint motion and distributed computation of tile humanoid, ISHURO, and suggest its result such as structure of the network and a disturbance observer.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2001.11a
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• pp.166-171
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• 2001

In order to improve the efficiency of the design process and the quality of the resulting design for the application-based exclusive rolling element bearings, this study propose design methodologies by using a genetic-based combinatorial optimization. By the presence of discrete variables such as the number of rolling element (standard component) and by the engineering point of views, the design problem of the rolling element bearing can be characterized by the combinatorial optimization problem as a fully discrete optimization. A genetic algorithm is used to efficiently find a set of the optimum discrete design values from the pre-defined variable sets. To effectively deal with the design constraints and the multi-objective problem, a ranking penalty method is suggested for constructing a fitness function in the genetic-based combinatorial optimization. To evaluate the proposed design method, a robust performance analyzer of ball bearing based on quasi-static analysis is developed and the computer program is applied to some design problems, 1) maximize fatigue life, 2) maximize stiffness, 3) maximize fatigue life and stiffness, of a angular contact ball bearing. Optimum design results are demonstrate the effectiveness of the design method suggested in this study. It believed that the proposed methodologies can be effectively applied to other multi-objective discrete optimization problems.

• Journal of Korean Society of Steel Construction
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• v.17 no.4 s.77
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• pp.385-394
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• 2005

In this paper, a discrete optimum design program was developed using the refined fuzzy-genetic algorithms based on the genetic algorithms and the fuzzy theory. The optimum design in this study can perform section and shape optimization simultaneously for planar and spatial steel structures. In this paper, the objective function is the weight of steel structures and the constraints are the design limits defined by the design and buckling strengths, displacements, and thicknesses of the member sections. The design variables are the dimensions and coordinates of the steel sections. Design examples are given to show the applicability of the discrete optimum design using the improved fuzzy-genetic algorithms in this study.

• Journal of Plant Biotechnology
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• v.46 no.2
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• pp.61-70
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• 2019

There is vast genetic diversity of Myanmar Mangoes. This study mainly focused on indigenous thirteen different mango landraces cultivated in central area of Myanmar, Kyauk-se District and their fruit characteristics by 18 descriptors together with genetic relationship among them by 12 SSR markers. Based on the morpho-physical characters, a wide variation among accessions was found. Genetic characterization of thirteen mango genotypes resulted in the detection of 302 scorable polymorphic bands with an average of 4.33 alleles per locus and an average polymorphism information content (PIC) of 0.7. All the genotypes were grouped into two major clusters by UPGMA cluster analysis and a genetic similarity was observed in a range of 61 ~ 85%. This study may somehow contribute insights into the identification of regional mango diversity in Myanmar and would be useful for future mango breeding program.