• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.111-113
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• 2004

Histogram Equalization is the most popular algorithm for contrast enhancement due to its effectiveness and simplicity. In this paper, We propose the advanced contrast enhancement method using genetic algorithm. We propose a novel objective criterion for enhancement, and attempt finding the best image according to the respective criterion. Due to the high complexity of the enhancement criterion proposed, we employ a Genetic Algorithm. We compared our method with other enhancement techniques, like Global Histogram Equalization and Partially Overlapped Sub-Block Histogram Equalization(POSHE).

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.140-146
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• 2019

Andrew Niccols's movie Gattaca (1997) inspired the formulation of the "Gattaca Argument" concerning the negative outcome of biotechnology, which has since been critiqued especially in the context of transhumanism and posthumanism. According this argument the development of genetic enhancement will produce a genetic discrimination and lead us to serious form of inequality. However, in particular transhumanists deny that here are reasons to worry and advocating instead the transformation of human condition in terms of genetic enhancement. Moreover, they question that genetic enhancement will necessarily lead to social inequality. In what follows, we will reexamine the Gattaca Argument and its critiques based on the movie in order to reassess the role the movie plays in the subsequent scholarly discussion. We will argue that existing critiques fall short of capturing the problem posed in the movie - the problem of the inhumane. Based on a hermeneutic approach to the movie we will both reconstruct the arguments and evaluate the transhuman counterarguments in terms of modern history of philosophical ideas.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.8
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• pp.360-367
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• 2002

In this paper, genetic algorithm based adaptive image enhancement filtering scheme is proposed and Implemented on FPGA board. Conventional filtering methods require a priori noise information for image enhancement. In general, if a priori information of noise is not available, heuristic intuition or time consuming recursive calculations are required for image enhancement. Contrary to the conventional filtering methods, the proposed filter system can find optimal combination of filters as well as their sequent order and parameter values adaptively to unknown noise types using structured genetic algorithms. The proposed image enhancement filter system is mainly composed of two blocks. The first block consists of genetic algorithm part and fitness evaluation part. And the second block consists of four types of filters. The first block (genetic algorithms and fitness evaluation blocks) is implemented on host computer using C code, and the second block is implemented on re-configurabe FPGA board. For gray scale control, smoothing and deblurring, four types of filters(median filter, histogram equalization filter, local enhancement filter, and 2D FIR filter) are implemented on FPGA. For evaluation, three types of noises are used and experimental results show that the Proposed scheme can generate optimal set of filters adaptively without a pioi noise information.

• Journal of Multimedia Information System
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• v.4 no.2
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• pp.89-92
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• 2017

This paper investigates simple gray level image enhancement technique based on Genetic Algorithms and Local Statistics. The task of GA is to adapt the parameters of local sliding masks over pixels, finding out the best parameters preserving the brightness and possibly preventing the creation of intensity artifacts in the local area of images. The algorithm is controlled by GA as to enhance the contrast and details in the images automatically according to an object fitness criterion. Results obtained in terms of subjective and objective evaluations, show the plausibility of the method suggested here.

• Plant Biotechnology Reports
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• v.5 no.1
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• pp.71-77
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• 2011

Drought and salinity are the most important abiotic stresses that affect the normal growth and development of plants. Glycine betaine is one of the most important osmolytes present in higher plants that enable them to cope with environmental stresses through osmotic adjustment. In this study, a betaine aldehyde dehydrogenase (BADH) gene from spinach under the control of the stress-induced promoter rd29A from Arabidopsis thaliana was introduced into potato cultivar Gannongshu 2 by the Agrobacterium tumefaciens system. Putative transgenic plants were confirmed by Southern blot analysis. Northern hybridization analysis demonstrated that expression of BADH gene was induced by drought and NaCl stress in the transgenic potato plants. The BADH activity in the transgenic potato plants was between 10.8 and 11.7 U. There was a negative relationship (y = -2.2083x + 43.329, r = 0.9495) between BADH activity and the relative electrical conductivity of the transgenic potato plant leaves. Plant height increased by 0.4-0.9 cm and fresh weight per plant increased by 17-29% for the transgenic potato plants under NaCl and polyethylene glycol stresses compared with the control potato plants. These results indicated that the ability of transgenic plants to tolerate drought and salt was increased when their BADH activity was increased.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2702-2719
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• 2013

A new optimal scheme based on curvelet transform is proposed for retinal image enhancement (RIE) using real-coded quantum genetic algorithm. Curvelet transform has better performance in representing edges than classical wavelet transform for its anisotropy and directional decomposition capabilities. For more precise reconstruction and better visualization, curvelet coefficients in corresponding subbands are modified by using a nonlinear enhancement mapping function. An automatic method is presented for selecting optimal parameter settings of the nonlinear mapping function via quantum genetic search strategy. The performance measures used in this paper provide some quantitative comparison among different RIE methods. The proposed method is tested on the DRIVE and STARE retinal databases and compared with some popular image enhancement methods. The experimental results demonstrate that proposed method can provide superior enhanced retinal image in terms of several image quantitative evaluation indexes.

• Journal of Electrical Engineering and Technology
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• v.7 no.4
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• pp.493-500
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• 2012

In this paper the performance of meta-heuristics algorithms such as GA (Genetic Algorithm), DE (Differential Evolution), PSO (Particle Swarm Optimization) and SA (Simulated Annealing) for the problem of TTC enhancement using FACTS devices are compared. In addition to that in the assessment procedure of TTC two novel techniques are proposed. First the optimization algorithm which is used for TTC enhancement is simultaneously used for assessment of TTC. Second the power flow is done using Broyden - Shamanski method with Sherman - Morrison formula (BSS). The proposed approach is tested on WSCC 9 bus, IEEE 118 bus test systems and the results are compared with the conventional Repeated Power Flow (RPF) using Newton Raphson (NR) method which indicates that the proposed method provides better TTC enhancement and computational efficacy than the conventional procedure.

• Animal cells and systems
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• v.14 no.1
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• pp.37-44
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• 2010

Black sea bream, Acanthopagrus schlegelii, is a commercially important fish in Korea. As a preliminary investigation into the effect of hatchery rearing for stock enhancement, we examined genetic diversity between wild and farmed black sea bream populations from Jeju using six microsatellite markers. High levels of polymorphism were observed between the two populations. A total of 87 different alleles were found at the loci, with some alleles being unique. Allelic variability ranged from 8 to 22 in the wild population and from 7 to 17 in the farmed one. Average observed and expected heterozygosities were estimated at 0.87 and 0.88 in the wild sample. The corresponding estimates were 0.83 and 0.86 in the farmed sample. Although a considerable loss of rare alleles was observed in the farmed sample, no statistically significant reductions were found in heterozygosity or allelic diversity in the farmed sample, compared with the wild one. Significant genetic heterogeneity was found between the wild and farmed populations. These results suggest that more intensive breeding practices for stock enhancement may have resulted in a further decrease of genetic diversity. Thus, it is necessary to monitor genetic variation in bloodstock, progeny, and target populations and control inbreeding in a commercial breeding program for conservation. This information may be useful for fisheries management and the aquaculture industry.

• Journal of Korea Water Resources Association
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• v.46 no.3
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• pp.267-276
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• 2013

An Improvement of channel structure for sound fish habitat suitability enhancement is investigated. The restoration target species of Zacco Koreanus which is represented a sound aquatic ecosystem is selected by investigating results of the fish fauna and the river environments. The changes of lower channel width for enhancing suitability indices for water velocity and depth result in habitat suitability enhancement in general by PHABSIM simulation. The habitat suitability enhancement is not guaranteed consistently by the changes of lower channel is confirmed. The optimal lower channel widths at each reach are presented by genetic algorithm of optimization which is considering the enhancement of suitability indices for water velocity and depth with given instream flows. The suggested plan of the lower channel modification will contribute to the various projects for the environmental improvement of aquatic system.

• Journal of Biomedical Engineering Research
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• v.21 no.5
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• pp.527-535
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• 2000

For a reliable patient set-up verification, better portal films are needed to track relevant features. Simulator films are compared with portal films as a reference image in radiotherapy planning. This shows some possibilities of the use of image information of simulator images for enhancement and restorations of portal images which are very poor in quality compared with the simulator images. This paper present an approach that combine an associative memory, a kind of artificial neural networks with fuzzy image enhancement technique using genetic algorithm which determines the fuzzy region of membership function by the use of maximum entropy principles. A higher portal image quality than conventional technique is achieved.