• 한국자원식물학회지
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• 제17권1호
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• pp.20-23
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• 2004

우리나라에 제주도와 남부도서지방 등지에 자생하고 있는 새우란을 신품종으로 육성하기 위 하여 우량계통을 1차 선발한 57개의 우수계통 중에서 화려한 꽃색과 향기를 지니고 있어 원예적 가치가 인정되어 신품종으로 선발 육성한 ‘색동’의 품종특성을 보면 다음과 같다. 색동의 꽃받침색은 밝은 주황색이고 꽃잎은 짙은 노란색으로 화려한 화색을 가졌으며, 순판색은 노란색으로 화색이 화려한 변이종이었다. 또한 방향성을 지니고 있었고 꽃피기는 안아피기 형태를 가지고 있었다.

• 대한기계학회논문집A
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• 제26권4호
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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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• 제46권2호
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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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• 제11권4호
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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.

• 대한전기학회논문지:전력기술부문A
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• 제48권7호
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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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• 제3권2호
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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.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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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.

• 노동경제논집
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• 제32권3호
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• pp.91-121
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• 2009

이 논문에서는 한국의 경우 개별 학군 내에서 사립학교와 공립학교 간에 학생 배분이 무작위로 이루어진다는 특수성을 이용하여, 사립학교가 공립학교에 비해 학생들의 성적향상 측면에서보다 효율적인지를 분석하기 위한 자연실험 분석을 실시하였다. 학군의 고정효과를 통제한 모델을 분석한 결과, 사립학교가 공립학교에 비해 학생들의 성적이 보다 향상된다는 통계적으로 유의미한 결과를 확인할 수 없었다. 단 상위 성적 계층의 여학생들의 경우, 사립학교 학생이 0.13 표준편차만큼 성적이 더 향상되는 것으로 나타났다.

• Smart Structures and Systems
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• 제26권4호
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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.

• 한국환경과학회지
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• 제20권11호
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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.