• 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 KAIS Fall Conference
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• 2003.11a
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• pp.80-83
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• 2003

A Genetic algorithm is a searching algorithm that based on the law of the survival of the fittest. Multi-population Genetic Algorithms are a modified form of genetic algorithm. Therefore, experience with fuzzy logic and genetic algorithm has proven to be that a combination of them can efficiently make up for their own deficiency. The Multi-population Genetic Algorithms independently evolve subpopulations. In this paper, we suggest a new coding method that independently evolves subpopulations using the fuzzy logic controller. The fuzzy logic controller has applied two fuzzy logic controllers that are implemented to adaptively adjust the crossover rate and mutation rate during the optimization process. The migration scheme in the multi-population genetic algorithms using fuzzy logic controllers is tested for a function optimization problem, and compared with other group migration schemes, therefore the groups migration scheme is then performed. The results demonstrate that the migration scheme in the multi-population genetic algorithms using fuzzy logic controller has a much better performance.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2004.11a
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• pp.221-221
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• 2004

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.1
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• pp.201-209
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• 2014

This paper proposes a genetic algorithm to maximize the connectivity among the mobile nodes for the cooperative communication in ad-hoc networks. In general, as the movement of the mobile nodes in the networks increases, the amount of calculation for finding the solution would be too much increased. To obtain the optimal solution within a reasonable computation time for a high-density network, we propose a genetic algorithm to obtain the optimal solution for maximizing the connectivity. In order to make a search more efficient, we propose some efficient neighborhood generating operations of the genetic algorithm. We evaluate those performances through some experiments in terms of the maximum number of connections and the execution time of the proposed algorithm. The comparison results show that the proposed algorithm outperforms other existing algorithms.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.6
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• pp.147-154
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• 2013

To provide a method for optimizing the variation range of the received power is applied to Adaptive Genetic Algorithm in a LED communication environment. By optimizing the power distribution dynamically for mobile or fixed using a genetic algorithm, to eliminate the need for a system design that is customized to be independent of the movement pattern of the user's adaptability, and environmental properties. It is possible to improve easily the convenience of the user. The room power deviation from any location can be reduced by reducing the energy. the simulation results, the proposed method does not exist obstacles in an empty room with power deviation $10.5{\mu}W$ decreased 10 percent to reduce the deviation of the received power is shown that. In comparison with conventional methods, convergence to the optimal value is improved, the genetic algorithm proposed was confirmed to be efficient in terms of energy savings.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.8
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• pp.1765-1772
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• 2015

In the underwater acoustic communication channels, multipath reflection become the cause of obstacle. Generally, equalizer has been applied to overcome these problems. In this paper, the method was proposed to optimize tap-length of decision feedback equalizer using genetic algorithm. After inputting feed-forward filter length and feed-back filter length as genetic information of the genetic algorithm, it optimize tap-length using BER(bit error rate) calculation in accordance with object function. The object function consist of decision feedback equalizer and BER calculation. For the purpose of BER calculation in the object function, the method was proposed to optimize the tap-length of decision feedback equalizer with genetic algorithm using preamble signals. As a result of experiments, the optimized BER is 0.0355 for signals which were received through a 25m receiver and which were applied to calculate BER merely using preamble signals in object function. When all data were used to calculate BER in object function, the optimized BER is 0.0215.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.209-212
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• 2005

Hyperspectral data consists of more than 200 spectral bands that are highly correlated. In order to utilize hyperspectral data for classification, dimensional reduction or feature extraction is desired. By applying feature extraction, computational complexity of classification can be reduced and classification accuracy may be improved. In this paper, a genetic algorithm based feature extraction technique is proposed. Measure from discriminant analysis is utilized as optimization criterion. A subset of spectral bands is selected by genetic algorithm. Dimension of feature space is further reduced by linear transformation. Feasibility of the proposed technique is evaluated with AVIRIS data.

• Journal of Communications and Networks
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• v.15 no.5
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• pp.486-495
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• 2013

In this article, we suggest a two-dimensional genetic algorithm (GA) method that applies a cognitive radio (CR) decision engine which determines the optimal transmission parameters for multicarrier communication systems. Because a CR is capable of sensing the previous environmental communication information, CR decision engine plays the role of optimizing the individual transmission parameters. In order to obtain the allowable transmission power of multicarrier based CR system demands interference analysis a priori, for the sake of efficient optimization, a two-dimensionalGA structure is proposed in this paper which enhances the computational complexity. Combined with the fitness objective evaluation standard, we focus on two multi-objective optimization methods: The conventional GA applied with the multi-objective fitness approach and the non-dominated sorting GA with Pareto-optimal sorting fronts. After comparing the convergence performance of these algorithms, the transmission power of each subcarrier is proposed as non-interference emission with its optimal values in multicarrier based CR system.

• Journal of the Optical Society of Korea
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• v.18 no.2
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• pp.118-123
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• 2014

For multi parameter optimization of Raman Fiber Amplifier (RFA), a simple genetic algorithm is presented in the scenario of a 320 channel Dense Wavelength Division Multiplexed (DWDM) system at channel spacing of 25 GHz. The large average gain (> 22 dB) is observed from optimized RFA with the optimized parameters, such as 39.6 km of Raman length with counter-propagating pumps tuned to 205.5 THz and 211.9 THz at pump powers of 234.3 mW, 677.1 mW respectively. The gain flattening filter (GFF) has also been optimized to further reduce the gain ripple across the frequency range from 190 to 197.975 THz for broadband amplification.

• 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.