• Title/Summary/Keyword: Genetic characteristic

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An intelligent semi-active isolation system based on ground motion characteristic prediction

  • Lin, Tzu-Kang;Lu, Lyan-Ywan;Hsiao, Chia-En;Lee, Dong-You
    • Earthquakes and Structures
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    • v.22 no.1
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    • pp.53-64
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    • 2022
  • This study proposes an intelligent semi-active isolation system combining a variable-stiffness control device and ground motion characteristic prediction. To determine the optimal control parameter in real-time, a genetic algorithm (GA)-fuzzy control law was developed in this study. Data on various types of ground motions were collected, and the ground motion characteristics were quantified to derive a near-fault (NF) characteristic ratio by employing an on-site earthquake early warning system. On the basis of the peak ground acceleration (PGA) and the derived NF ratio, a fuzzy inference system (FIS) was developed. The control parameters were optimized using a GA. To support continuity under near-fault and far-field ground motions, the optimal control parameter was linked with the predicted PGA and NF ratio through the FIS. The GA-fuzzy law was then compared with other control laws to verify its effectiveness. The results revealed that the GA-fuzzy control law could reliably predict different ground motion characteristics for real-time control because of the high sensitivity of its control parameter to the ground motion characteristics. Even under near-fault and far-field ground motions, the GA-fuzzy control law outperformed the FPEEA control law in terms of controlling the isolation layer displacement and the superstructure acceleration.

Differential Response to Growth Regulator of Tobacco Crown Gall Tumor and Genetic Tumor (연초 Crown Gall Tumor 와 Genetic Tumor의 식물호르몬에 대한 분화반응)

  • 양덕춘;정재훈;민병훈;최광태;이정명
    • Korean Journal of Plant Tissue Culture
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    • v.26 no.1
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    • pp.31-35
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    • 1999
  • Morphological characteristic during formation of tobacco crown gall tumor and genetic tumor, and their differential response to growth regulator were investigated in in vitro culture. Crown gall tumor was induced from tumor tissue transformed by infecting Agrobacterium tumefaciens C58. Genetic tumor was induced from tumor tissue which was induced spontaneously from reciprocal interspecific hybrids between Nicotiana glauca (2n=24) and Nicotiana langsdorffii (2n=18). Morphological characteristic of crown gall tumor, genetic tumor, and teratoma shoot was very similar, and they were actively proliferated on hormone-free medium. Typical tumor callus and teratoma shoot formed from crown gall tumor on the hormone-free medium. On the contrary, tumor callus derived from genetic tumor formed as a crown gall tumor callus on the medium supplemented with 0.5 mg/L of 2,4-D, and lots of teratoma shoots without any root formed on the hormone-free medium. Root development from the teratoma shoots was hardly obtained on the medium with IAA, GA and active carbon. However, teratoma shoots with roots, as normal shoots, were initiated occasionally on the hormone-free medium. These shoots also formed new genetic tumor on the stem, which leaves formed lots of teratoma shoot on the hormone-free medium in in vitro culture.

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An Improved Function Synthesis Algorithm Using Genetic Programming (유전적 프로그램을 이용한 함수 합성 알고리즘의 개선)

  • Jung, Nam-Chae
    • Journal of the Institute of Convergence Signal Processing
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    • v.11 no.1
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    • pp.80-87
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    • 2010
  • The method of function synthesis is essential when we control the systems not known their characteristic, by predicting the function to satisfy a relation between input and output from the given pairs of input-output data. In general the most systems operate non-linearly, it is easy to come about problem is composed with combinations of parameter, constant, condition, and so on. Genetic programming is proposed by one of function synthesis methods. This is a search method of function tree to satisfy a relation between input and output, with appling genetic operation to function tree to convert function into tree structure. In this paper, we indicate problems of a function synthesis method by an existing genetic programming propose four type of new improved method. In other words, there are control of function tree growth, selection of local search method for early convergence, effective elimination of redundancy in function tree, and utilization of problem characteristic of object, for preventing function from complicating when the function tree is searched. In case of this improved method, we confirmed to obtain superior structure to function synthesis method by an existing genetic programming in a short period of time by means of computer simulation for the two-spirals problem.

Development of an User Interface Design Method using Adaptive Genetic Algorithm (적응형 유전알고리즘을 이용한 사용자 인터페이스 설계 방법 개발)

  • Jung, Ki-Hyo
    • Journal of Korean Institute of Industrial Engineers
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    • v.38 no.3
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    • pp.173-181
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    • 2012
  • The size and layout of user interface components need to be optimally designed in terms of reachability, visibility, clearance, and compatibility in order for efficient and effective use of products. The present study develops an ergonomic design method which optimizes the size and layout of user interface components using adaptive genetic algorithm. The developed design method determines a near-optimal design which maximizes the aggregated score of 4 ergonomic design criteria (reachability, visibility, clearance, and compatibility). The adaptive genetic algorithm used in the present study finds a near-optimum by automatically adjusting the key parameter (probability of mutation) of traditional genetic algorithm according to the characteristic of current solutions. Since the adaptive mechanism partially helps to overcome the local optimality problem, the probability of finding the near-optimum has been substantially improved. To evaluate the effectiveness of the developed design method, the present study applied it to the user interface design for a portable wireless communication radio.

Progress, challenges, and future perspectives in genetic researches of stuttering

  • Kang, Changsoo
    • Journal of Genetic Medicine
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    • v.18 no.2
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    • pp.75-82
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    • 2021
  • Speech and language functions are highly cognitive and human-specific features. The underlying causes of normal speech and language function are believed to reside in the human brain. Developmental persistent stuttering, a speech and language disorder, has been regarded as the most challenging disorder in determining genetic causes because of the high percentage of spontaneous recovery in stutters. This mysterious characteristic hinders speech pathologists from discriminating recovered stutters from completely normal individuals. Over the last several decades, several genetic approaches have been used to identify the genetic causes of stuttering, and remarkable progress has been made in genome-wide linkage analysis followed by gene sequencing. So far, four genes, namely GNPTAB, GNPTG, NAGPA, and AP4E1, are known to cause stuttering. Furthermore, thegeneration of mouse models of stuttering and morphometry analysis has created new ways for researchers to identify brain regions that participate in human speech function and to understand the neuropathology of stuttering. In this review, we aimed to investigate previous progress, challenges, and future perspectives in understanding the genetics and neuropathology underlying persistent developmental stuttering.

The Design of Optimized Fuzzy Cascade Controller: Focused on Type-2 Fuzzy Controller and HFC-based Genetic Algorithms (최적 퍼지 직렬형 제어기 설계: Type-2 퍼지 제어기 및 공정경쟁기반 유전자알고리즘을 중심으로)

  • Kim, Wook-Dong;Jang, Han-Jong;Oh, Sung-Kwun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.59 no.5
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    • pp.972-980
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    • 2010
  • In this study, we introduce the design methodology of an optimized type-2 fuzzy cascade controller with the aid of hierarchical fair competition-based genetic algorithm(HFCGA) for ball & beam system. The ball & beam system consists of servo motor, beam and ball, and remains mutually connected in line in itself. The ball & beam system determines the position of ball through the control of a servo motor. Consequently the displacement change of the position of the moving ball and its ensuing change of the angle of the beam results in the change of the position angle of a servo motor. The type-2 fuzzy cascade controller scheme consists of the outer controller and the inner controller as two cascaded fuzzy controllers. In type-2 fuzzy logic controller(FLC) as the expanded type of type-1 fuzzy logic controller(FLC), we can effectively improve the control characteristic by using the footprint of uncertainty(FOU) of membership function. The control parameters(scaling factors) of each fuzzy controller using HFCGA which is a kind of parallel genetic algorithms(PGAs). HFCGA helps alleviate the premature convergence being generated in conventional genetic algorithms(GAs). We estimated controller characteristic parameters of optimized type-2 fuzzy cascade controller applied ball & beam system such as maximum overshoot, delay time, rise time, settling time and steady-state error. For a detailed comparative analysis from the viewpoint of the performance results and the design methodology, the proposed method for the ball & beam system which is realized by the fuzzy cascade controller based on HFCGA, is presented in comparison with the conventional PD cascade controller based on serial genetic algorithms.

A Study on the Vibration Minimization for Realizing the High-Speed and Flexible Motion in BLDC Motor of Robot (고속 유연한 로봇 운동 구현을 위한 BLDC Motor의 진동 최소화 설계)

  • Lee Dong-Yeup;Kim Gyu-Tak;Jung Won-Ji;Kim Sung-Hyun
    • The Transactions of the Korean Institute of Electrical Engineers B
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    • v.54 no.7
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    • pp.329-334
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    • 2005
  • This paper presents the optimal design for reducing the rotor inertia in order to improve the driving characteristic of BLDC motor for robots. The parallel Genetic Algorithm is performed to rotor inertia minimization in optimal design. Also, velocity profile with finite jerk method is introduced to reduce vibration of BLDC motor. As a result, a torque characteristic is same although rotor inertia is reduced to 2/3 compared with prototype model. And, maximum vibration value is reduced by 63.4[$\%$] according to the application of finite .jerk method.

Optimal Parameter Selection of Power System Stabilizer using Genetic Algorithm (유전 알고리즘을 이용한 전력시스템 안정화 장치의 최적 파라미터 선정)

  • Chung, Hyeng-Hwan;Wang, Yong-Peel;Chung, Dong-Il;Chung, Mun-Kyu
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.48 no.6
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    • pp.683-691
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    • 1999
  • In this paper, it is suggested that the selection method of optimal parameter of power system stabilizer(PSS) with robustness in low frequency oscillation for power system using Real Variable Elitism Genetc Algorithm(RVEGA). The optimal parameters were selected in the case of power system stabilizer with one lead compensator, and two lead compensator. Also, the frequency responses characteristic of PSS, the system eigenvalues criterion and the dynamic characteristic were considered in the normal load and the heavy load, which proved usefulness of RVEGA compare with Yu's compensator design theory.

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Effective Robot Path Planning Method based on Fast Convergence Genetic Algorithm (유전자 알고리즘의 수렴 속도 향상을 통한 효과적인 로봇 길 찾기 알고리즘)

  • Seo, Min-Gwan;Lee, Jae-Sung;Kim, Dae-Won
    • Journal of the Korea Society of Computer and Information
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    • v.20 no.4
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    • pp.25-32
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    • 2015
  • The Genetic algorithm is a search algorithm using evaluation, genetic operator, natural selection to populational solution iteratively. The convergence and divergence characteristic of genetic algorithm are affected by selection strategy, generation replacement method, genetic operator when genetic algorithm is designed. This paper proposes fast convergence genetic algorithm for time-limited robot path planning. In urgent situation, genetic algorithm for robot path planning does not have enough time for computation, resulting in quality degradation of found path. Proposed genetic algorithm uses fast converging selection strategy and generation replacement method. Proposed genetic algorithm also uses not only traditional crossover and mutation operator but additional genetic operator for shortening the distance of found path. In this way, proposed genetic algorithm find reasonable path in time-limited situation.