• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.6
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• pp.547-557
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• 2016

Due to threats caused by social disasters, operating surveillance devices are essential for social safety. CCTV, infrared cameras and other surveillance equipment are used to observe threats. This research proposes a method for searching for the optimum location of surveillance sensors. A GA (Genetic Algorithm) was used, since this algorithm is one of the most reasonable and efficient methods for solving complex non-linear problems. The sensor specifications, a DEM (Digital Elevation Model) and VITD (Vector Product Interim Terrain Data) maps were used for input data. We designed a chromosome using the sensor pixel location, and used elitism selection and uniform crossover for searching final solution. A fitness function was derived by the number of detected pixels on the borderline and the sum of the detection probability in the surveillance zone. The results of a 5-sensor and a 10-sensor were compared and analyzed.

• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.501-506
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• 2002

In this study, a novel systematic design procedure by Genetic Algorithm of a two stage relief valve is proposed. First of all. a mathematical model describing the dynamics of a balanced piston type relief valve has been derived. Governing equations such as dynamic equations for the main spool and the pilot spool and flow equations for each orifice are established. The mathematical model is verified by comparing the results of simulation with that of experiments. Furthermore, influences of the parameters on the dynamic characteristics of a relief valve have been investigated by simulation of the proposed model. Major design parameters on the valve response are determined, which affect the system response significantly. And then, using the determined parameters, the optimization of the two stage relief valve by Genetic Algorithm, which is a random search algorithm can find the global optimum without converging local optimum, is performed. The optimal design process of a two stage relief valve is presented to determine the major design parameters. Fitness function reflects the changing pressure according to parameters. It is shown that the genetic algorithms satisfactorily optimized the major design parameters of the two stage relief valve.

• Journal of Fashion Business
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• v.24 no.4
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• pp.48-62
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• 2020

Originating in South Korea, Taekwondo has been globally popular among individuals who desire to improve their health in a unique fashion. The Taekwondo uniform, one of the essential factors within the sport, needs to possess both functionality and size suitability to support dynamic movements within Taekwondo. This study investigated the development of patterns in Taekwondo uniforms by suggesting patterns that reflect physical suitability derived from appearance tests and movement functionality tests of the uniforms. More specifically, we selected a sample uniform and conducted a dressing test, which considered both the aesthetics and the functionality of the garment. Then, we considered size suitability, which allowed us to design practical Taekwondo uniform patterns that encompassed more variation in body sizes of both men and women. The result of the dressing test was that women's uniforms typically required more factors compared to men's uniforms due to women's relatively smaller physiques. Based on this result, we revised the pattern to also encompass the minor differences in uniforms between men and women. In the end, the Taekwondo uniforms for women required more modifications than those for men.

• Journal of Korean Association for Spatial Structures
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• v.1 no.1 s.1
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• pp.125-134
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• 2001

The objective of this study is the development of size discrete optimum design algorithm which is based on the GAs(genetic algorithms). The algorithm can perform size discrete optimum designs of space trusses. The developed algorithm was implemented in a computer program. For the optimum design, the objective function is the weight of space trusses and the constraints are limite state design codes(1998) and displacements. The basic search method for the optimum design is the GAs. The algorithm is known to be very efficient for the discrete optimization. This study solves the problem by introducing the GAs. The GAs consists of genetic process and evolutionary process. The genetic process selects the next design points based on the survivability of the current design points. The evolutionary process evaluates the survivability of the design points selected from the genetic process. In the genetic process of the simple GAs, there are three basic operators: reproduction, cross-over, and mutation operators. The efficiency and validity of the developed discrete optimum design algorithm was verified by applying GAs to optimum design examples.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.2
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• pp.194-198
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• 2004

This paper presents a broadband compact microstrip antenna design with four U slots on the ground plane by using of genetic algorithm. FDTD method is used as fitness function for antenna analysis, and length of rectangular patch, length of ground plane slot, distance from center point to feed point is used as optimization parameter for maximum bandwidth and minimum size. The measurement result of implemented antenna present 10 dB bandwidth of 15.63 ％ and peak gain of 3.61 dBi in the 2.445 GHz, and antenna has a reduced patch size of 54.8 ％ compare with normal microstrip antenna.

• Proceedings of the KIEE Conference
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• 1994.07a
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• pp.165-167
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• 1994

This paper presents a new method for multiobjective optimization using Genetic Algorithm-Sexual Reproduction Model(SR model). In SR model, each individual consists of chromosome pairs. Sex cells(gametes) are produced through artificial meiosis in which crossover and mutation occur, The proposed method has two selection operators, one, individual selection which selects the individual to fertilize, and the other, gamete selection which makes zygote for offspring production, The two selection schemes are repectively conducted according to different fitness(or objective) function and consequently give a solution which is unbiased to any objectives. We apply the proposed method to optimization of the design parameters of Linear Induction Motor(LIM) and show its effectiveness.

• 전자공학회논문지 IE
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• v.46 no.2
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• pp.7-10
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• 2009

This paper presents the implementation of libraries of hardware modules for genetic algorithm using VHDL. Evolvable hardware refers to hardware that can change its architecture and behavior dynamically and autonomously by interacting with its environment. So, it is especially suited to applications where no hardware specifications can be given in advance. Evolvable hardware is based on the idea of combining reconfigurable hardware device with evolutionary computation, such as genetic algorithm. Because of parallel, no function call overhead and pipelining, a hardware genetic algorithm give speedup over a software genetic algorithm. This paper suggests the hardware genetic algorithm for evolvable embedded system chip. That includes simulation results and analysis for several fitness functions. It can be seen that our design works well for the three examples.

• Journal of Korean Academy of Rural Health Nursing
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• v.12 no.1
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• pp.13-27
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• 2017

Purpose: The purpose of this study is to identify health-related factors, especially for the elderly who are subject to visiting health care at vulnerable populations. Methods: Tools were Guide to Community Integrated Health Promotion Project 2016, Visit Health Care Health Interview Survey, measures of physical function, motor skills, composite mobility, BMI, and subjective fitness levels. Depression was measured with the Short Results: Older elders living alone were more vulnerable than those with living others. Elders with less education showed greater weakness but the difference was not significant. Average scores for frailty were 2.21 (healthy group), 7.66 (high-risk group) and 15.69 (frail group). Scores based on weakness level differed significantly with the exception of nutrition. Nine out of 10 elders in disadvantaged areas were in the frail group or at high risk. Conclusion: Results support the goal to maintain/improve physical/mental functions through individual management of high-risk/frail older adults at risk of becoming infirm. It is imperative to implement a public health care delivery system to ensure programs are operated effectively and personalized.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.466-468
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• 2002

This paper proposes a new type of evolvable hardware for implementing the clone of Moore State machine. The proposed Evolvable Hardware is employed efficient pipeline parallelization, handshaking mechanism and fitness function in FPGA Genetic Algorithm(GA) has known as a method of solving NP problem in various applications. Since a major drawback of the GA is that it needs a long computation time, the hardware implementation of Genetic Algorithm is focused on in recent studies. Conventional hardware GA uses the fired length of chromosome but the proposed Evolvable Hardware uses the variable length of chromosome by the efficient 16 bit Pipeline Unit. Experimental results show that the proposed evolvable hardware is applicable to the implementation of the clone for Moore State machine