• Korean Journal of Plant Resources
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• v.17 no.1
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• pp.20-23
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• 2004

These studies were carried out to develop native Calanthe in Korea. Calanthe native to southern islands in korea has beautiful flowers with various color and sweet fragrance, and it has been reported to have very good ornamental value. Concerning the classified 57 lines had surveyed their characteristics during the three years, and confirmed which that had manifestation stably. And then, a line was developed and given a name of horticultural cultivar to ‘Saegdong’. The major characteristics of the selected line, ‘Saegdong’, were as follows. In its color of flower, sepal was reddish orange, petal was yellow and lip was yellow. ‘Saegdong’ had a bended-inner blooming type.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.4
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• pp.701-710
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• 2002

The framework, described in this paper, involves artificial evolutionary systems that re -produce aimed solutions through a simulated Darwinian evolution process. Through this process the framework designs structures of machines innovatively and emergently especially in the stages of conceptual and basic design. Since the framework simulates the evolution of nature, it inevitably involves processes that converse the natural evolution to the artificial evolution. For the conversion, based on several methods as the building block modeling, Artificial Life, evolutionary computation and the law of natural selection, we propose a series of processes that consists of modeling, evaluation, selection, evolution etc. We have demonstrated the implementation of the framework with the design of multi-step gear systems.

• ETRI Journal
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• v.46 no.2
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• pp.250-262
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• 2024

Air-writing recognition is relevant in areas such as natural human-computer interaction, augmented reality, and virtual reality. A trajectory is the most natural way to represent air writing. We analyze the recognition accuracy of words written in air considering five features, namely, writing direction, curvature, trajectory, orthocenter, and ellipsoid, as well as different parameters of a hidden Markov model classifier. Experiments were performed on two representative datasets, whose sample trajectories were collected using a Leap Motion Controller from a fingertip performing air writing. Dataset D₁ contains 840 English words from 21 classes, and dataset D₂ contains 1600 English words from 40 classes. A genetic algorithm was combined with a hidden Markov model classifier to obtain the best subset of features. Combination ftrajectory, orthocenter, writing direction, curvatureg provided the best feature set, achieving recognition accuracies on datasets D₁ and D₂ of 98.81% and 83.58%, respectively.

• Journal of Computing Science and Engineering
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• v.11 no.4
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• pp.121-129
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• 2017

Feature selection has been widely established as an efficient technique for microarray data analysis. Feature selection aims to search for the most important feature/gene subset of a given dataset according to its relevance to the current target. Unsupervised feature selection is considered to be challenging due to the lack of label information. In this paper, we propose a novel method for unsupervised feature selection, which incorporates embedded learning and $l_{2,1}-norm$ sparse regression into a framework to select genes in microarray data analysis. Local tangent space alignment is applied during embedded learning to preserve the local data structure. The $l_{2,1}-norm$ sparse regression acts as a constraint to aid in learning the gene weights correlatively, by which the proposed method optimizes for selecting the informative genes which better capture the interesting natural classes of samples. We provide an effective algorithm to solve the optimization problem in our method. Finally, to validate the efficacy of the proposed method, we evaluate the proposed method on real microarray gene expression datasets. The experimental results demonstrate that the proposed method obtains quite promising performance.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.7
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• pp.889-897
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• 1999

In this paper, we propose a new method of path planning for autonomous mobile robot in mapped circumstance. To search the optimal path, we adopt the genetic algorithm which is based on the natural mechanics of selection, crossover and mutation. We propose a method for generating the path population, selection and evaluation in genetic algorithm. Simulations show the efficiency for the global path planning, if we adopt the proposed GA method

• Journal of Microbiology and Biotechnology
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• v.3 no.2
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• pp.78-85
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• 1993

In order to elucidate the mechanism which regulates the production of cyclodextrin glucanotransferase (CGTase) and to achieve overproduction of CGTase by releasing catabolite (glucose) repression, several catabolite repression resistant mutants were selected from newly screened Bacillus firmus var. alkalophilus H609, after NTG (N-methyl-N -nitro-N-nitrosoguanidine) treatment, using 2-deoxyglucose as a nonmetabolizable analog of catabolite glucose and as a selection marker. Five catabolite repression resistant mutants were selected from about 30, 000 2-deoxyglucose resistant colonies. Relative catabolite repression indices of the selected mutants were in the range of 8~80% assuming 100% for parent strain. The amount of CGTase produced by the mutant strain CR41, which was 250 units/ml, was three times larger than that produced by its parent strain. The mutation seems to have occurred in the regulatory region of CGTase gene and not in the structural region or the glucose transporting system in cell membrane. The enzymatic properties of CGTase excreted from parent and mutant strains were also compared.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.393-396
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• 1995

In this syudy, the researches classifying the artificial and natural flaws in welding parts are performed using the smart pattern recognition technology. For this purpose the smart signal pattern recognition package including the user defined function was developed and the total procedure including the digital signal processing,feature extraction , feature selection and classifier selection is treated by bulk. Specially it is composed with and discussed using the statistical classifier such as the linear disciminant function classifier, the empirical Bayesian classifier. Also, the smart pattern recognition technology is applied to classification problem of natural flaw(i.e multiple classification problem-crack,lack of penetration,lack of fusion,porosity,and slag inclusion, the planar and volumetric flaw classification problem). According to this results, if appropriately learned the neural network classifier is better than ststistical classifier in the classification problem of natural flaw. And it is possible to acquire the recognition rate of 80% above through it is different a little according to domain extracting the feature and the classifier.

• Journal of Labour Economics
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• v.32 no.3
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• pp.91-121
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• 2009

Utilizing the fact that student allocation to private or public high schools in Korea is done randomly within a given school district, this study conducted a natural experiment, free from selection bias, to analyze whether private schools are more effective than public schools in terms of enhancing students' academic performance. After analyzing a model that controls the fixed effects of school districts, it was found that private schools do not have a statistically significant impact compared to public schools with respect to improving academic records. Nevertheless, the private school effect has shown a positive value equivalent to 0.13 standard deviation for female students at the highest academic levels.

• Smart Structures and Systems
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• v.26 no.4
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• pp.419-433
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• 2020

Investigation of structural integrity has been a critical issue in the field of civil engineering for years. Visual inspection is one of the most available methods to explore deteriorative components in structures. Still, this method is not applicable to invisible damage of structures. Alternatively, system identification methods are capable of tracking modal properties of structures over time. The deviation of these dynamic properties can serve as indicators to access structural integrity. In this study, a modal tracking technique using frequency-domain system identification from seismic responses of structures is proposed. The method first segments the measured signals into overlapped sequential portions and then establishes multiple Hankel matrices. Each Hankel matrix is then converted to the frequency domain, and a temporal-average frequency-domain Hankel matrix can be calculated. This study also proposes the frequency band selection that can divide the frequency-domain Hankel matrix into several portions in accordance with referenced natural frequencies. Once these referenced natural frequencies are unavailable, the first few right singular vectors by the singular value decomposition can offer these references. Finally, the frequency-domain stochastic subspace identification tracks the natural frequencies and mode shapes of structures through quick stabilization diagrams. To evaluate performance of the proposed method, a numerical study is carried out. Moreover, the long-term monitoring strong motion records at a specific site are exploited to assess the tracking performance. As seen in results, the proposed method is capable of tracking modal properties through seismic responses of structures.

• Journal of Environmental Science International
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• v.20 no.11
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• pp.1457-1464
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• 2011

In this study, the method of estimating hydrologic information (water depth, submerged period etc.) on the proper selection of construction point and scale as well as vegetation type suggested for the design of natural riparian rehabilitation structure. Long-term comprehensive watershed model SWAT-K(Korea) was applied to this purpose. Flow duration analysis was conducted to analyze the hydrologic characteristics of Pyungchang watershed at which the 'bangtul' construction method was tested. For this purpose 20 years (1989-2008) rainfall runoff analysis was carried out. Based on the simulated daily streamflow data, flow duration curve was made to analyze the flow characteristics, and the water depth hydrograph was made to analyze the water depth distribution at the cross section. Finally, the information for the selection of proper vegetation according to the submerged period is suggested.