• Title/Summary/Keyword: natural selection

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고속도로 현장별 비점오염 저감시설 선정방안 연구 (A Study for selecting the Highway Sites' Best Management Practice for Nonpoint Source Pollution)

  • 이용복;최상일;박계수;성일종;정선국
    • 환경영향평가
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    • 제20권6호
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    • pp.857-866
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    • 2011
  • This research categorized EIA target highways into following three types in order to minimize non-point source pollution from highway runoff. 1. Big drainage basin. 2. Small drainage basin. 3. Bridge section. The Natural, Filter and Swirl-Type devices were evaluated in terms of removal efficiency of TSS, BOD, COD, T-N, T-P, compatibility of site selection, economic feasibility, and maintenance convenience through which the final BMP was selected. According to the removal efficiency result, the area of Big and Small Drainage basin and bridge section had higher removal efficiency with natural facility than that of the Filter or Swirl-Type device. To make appropriate selection of highways'BMP for non-point source pollution, this study will aim to contribute to building more environmentally friendly highways by proposing the selection process that is made of 5 stages. 1. Selecting the target drainage basin. 2. Selecting the land for the mitigation facility. 3. Analysing the ease of maintenance. 4. Technically evaluating each installation. 5. Evaluating the effective implementation methods.

굴 수하식 양식에 있어 종묘의 선택이 수익성에 미치는 영향 (The Effects of the Oyster Seed Selection on Profitability of the Oyster Aquaculture Business)

  • 박영병
    • 수산경영론집
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    • 제28권2호
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    • pp.87-105
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    • 1997
  • The objective of this study is to analyze the effects of the oyster seed selection on profitability of the oyster aquaculture business The results of the analysis are as follows ; 1) The comparison of profitability among four different oyster seed applied to the four different scale : 1ha, 3ha, 5ha, and 10ha. The results of the comparison show that, for all scale, the artificial oyster seed is more profitable than the natural oyster seed or the natural oyster seed imported from Japan. 2) There are four important determinant variables of profitability to aquaculture business. In the order of their effect, it is oyster price, quantity of production, labor cost, and seed price. 3) If differences of price between the artificial hardening oyster seed and the natural hardening oyster seed are more less 1,430 won, the former is better. 4) The effect of increasing income of fishermen are estimated about 58.5 billion won or 102 billion won from the artificial oyster seed on the oyster aquaculture.

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Training Molecularly Enabled Field Biologists to Understand Organism-Level Gene Function

  • Kang, Jin-Ho;Baldwin, Ian T.
    • Molecules and Cells
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    • 제26권1호
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    • pp.1-4
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    • 2008
  • A gene's influence on an organism's Darwinian fitness ultimately determines whether it will be lost, maintained or modified by natural selection, yet biologists have few gene expression systems in which to measure whole-organism gene function. In the Department of Molecular Ecology at the Max Planck Institute for Chemical Ecology we are training "molecularly enabled field biologists" to use transformed plants silenced in the expression of environmentally regulated genes and the plant's native habitats as "laboratories." Research done in these natural laboratories will, we hope, increase our understanding of the function of genes at the level of the organism. Examples of the role of threonine deaminase and RNA-directed RNA polymerases illustrate the process.

초음파신호의 신경망 형상인식법을 이용한 오스테나이트 스테인레스강의 용접부결함 분류에 관한 연구 (Classification of Welding Defects in Austenitic Stainless Steel by Neural Pattern Recognition of Ultrasonic Signal)

  • 이강용;김준섭
    • 대한기계학회논문집A
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    • 제20권4호
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    • pp.1309-1319
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    • 1996
  • The research for the classification of the natural defects in welding zone is performd using the neuro-pattern recognition technology. The signal pattern recognition package including the user's defined function is developed to perform the digital signal processing, feature extraction, feature selection and classifier selection, The neural network classifier and the statistical classifiers such as the linear discriminant function classifier and the empirical Bayesian calssifier are compared and discussed. The neuro-pattern recognition technique is applied to the classificaiton of such natural defects as root crack, incomplete penetration, lack of fusion, slag inclusion, porosity, etc. If appropriately learned, the neural network classifier is concluded to be better than the statistical classifiers in the classification of the natural welding defects.

자연자원 보전지역의 평가모형 - 내셔널 트러스트 후보지 선정을 중심으로 - (The Evaluation Model for Natural Resource Conservation Areas - Focused on Site Selection for the National Trust -)

  • 유주한;정성관
    • 한국조경학회지
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    • 제30권2호
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    • pp.39-49
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    • 2002
  • The purpose of this study is to propose an objective and rational methodology for the selection of proposed sites far the National Trust(NT), which is the new alterative proposal far the conservation of natural environments destroyed by injudicious land development and economic growth. That is to enforce many analysis for the effective estimation of rare ecological and landscape resources and to propose a model based on estimation and united indicators. Using the estimative model, we apply it to the selection of the proposed site in micro scale and simultaneously offer the basic methodology of effective and systematic land conservation in macro scale. The results of this study are as follows: 1) The results of analysis for the reliability of estimative items and indicators, presented no problem in that the coefficient of reliability was over 0.7. 2) The correlation measure of the estimative indicator indicated that 'succession'and 'regenerating restorability' were highly correlative in the item of plants. Another three items showed a tendency to be alike. 3) The results of factor analysis on the characteristics of indicators, classified plants into four categories including a stable factor. The item of animals was classified as a stable and rare factor. The item of landscape was classified as a physical and mental factor and the environment as a pollutional and conditional factor. 4) The model of estimation created through factor analysis was valid for the approval of the regression model because significant probability was 0.00. When we consider the NT proposed site as a complex body that is composed of diverse natural and manmade resources, certainly the synthetic methodology of estimation is needed. If these studies are carried out, NT sites will be selected more rationally and effectively than at present. Consequently, they have the potential to play a core role of natural ecosystem conservation in Korea.

NOTES ON SELECTION PRINCIPLES IN TOPOLOGY (I): PARACOMPACTNESS

  • BABINKOSTOVA L.;KOCINAC LJ. D. R.;SCHEEPERS M.
    • 대한수학회지
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    • 제42권4호
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    • pp.709-721
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    • 2005
  • G. Gruenhage gave a characterization of paracompactness of locally compact spaces in terms of game theory ([6]). Starting from that result we give another such characterization using a selective version of that game, and study a selection principle in the class of locally compact spaces and its relationships with game theory and a Ramseyan partition relation. We also consider a selective version of paracompactness.

Variable Bandwidth Selection for Kernel Regression

  • Kim, Dae-Hak
    • Journal of the Korean Data and Information Science Society
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    • 제5권1호
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    • pp.11-20
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    • 1994
  • In recent years, nonparametric kernel estimation of regresion function are abundant and widely applicable to many areas of statistics. Most of modern researches concerned with the fixed global bandwidth selection which can be used in the estimation of regression function with all the same value for all x. In this paper, we propose a method for selecting locally varing bandwidth based on bootstrap method in kernel estimation of fixed design regression. Performance of proposed bandwidth selection method for finite sample case is conducted via Monte Carlo simulation study.

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Low Levels of Polymorphisms and Negative Selection in Plasmodum knowlesi Merozoite Surface Protein 8 in Malaysian Isolates

  • Ahmed, Md Atique;Kang, Hae-Ji;Quan, Fu-Shi
    • Parasites, Hosts and Diseases
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    • 제57권4호
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    • pp.445-450
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    • 2019
  • Human infections due to the monkey malaria parasite Plasmodium knowlesi is increasingly being reported from most Southeast Asian countries specifically Malaysia. The parasite causes severe and fatal malaria thus there is a need for urgent measures for its control. In this study, the level of polymorphisms, haplotypes and natural selection of full-length pkmsp8 in 37 clinical samples from Malaysian Borneo along with 6 lab-adapted strains were investigated. Low levels of polymorphism were observed across the full-length gene, the double epidermal growth factor (EGF) domains were mostly conserved, and non-synonymous substitutions were absent. Evidence of strong negative selection pressure in the non-EGF regions were found indicating functional constrains acting at different domains. Phylogenetic haplotype network analysis identified shared haplotypes and indicated geographical clustering of samples originating from Peninsular Malaysia and Malaysian Borneo. This is the first study to genetically characterize the full-length msp8 gene from clinical isolates of P. knowlesi from Malaysia; however, further functional characterization would be useful for future rational vaccine design.

자연 프루닝과 베이시안 선택에 의한 신경회로망 일반화 성능 향상 (Improving Generalization Performance of Neural Networks using Natural Pruning and Bayesian Selection)

  • 이현진;박혜영;이일병
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제30권3_4호
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    • pp.326-338
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    • 2003
  • 신경회로망 설계 및 모델선택의 목표는 최적의 구조를 가지는 일반화 성능이 우수한 네트워크를 구성하는 것이다. 하지만 학습데이타에는 노이즈(noise)가 존재하고, 그 수도 충분하지 않기 때문에 최종적으로 표현하고자 하는 진확률 분포와 학습 데이타에 의해 표현되는 경험확률분포(empirical probability density) 사이에는 차이가 발생한다. 이러한 차이 때문에 신경회로망을 학습데이타에 대하여 과다하게 적합(fitting)시키면, 학습데이타만의 확률분포를 잘 추정하도록 매개변수들이 조정되어 버리고, 진확률 분포로부터 멀어지게 된다. 이러한 현상을 과다학습이라고 하며, 과다학습된 신경회로망은 학습데이타에 대한 근사는 우수하지만, 새로운 데이타에 대한 예측은 떨어지게 된다. 또한 신경회로망의 복잡도가 증가 할수록 더 많은 매개변수들이 노이즈에 쉽게 적합되어 과다학습 현상은 더욱 심화된다. 본 논문에서는 통계적인 관점을 바탕으로 신경회로망의 일반화 성능을 향상시키는 신경회로 망의 설계 및 모델 선택의 통합적인 프로세스를 제안하고자 한다. 먼저 학습의 과정에서 적응적 정규화가 있는 자연기울기 학습을 통해 수렴속도의 향상과 동시에 과다학습을 방지하여 진확률 분포에 가까운 신경회로망을 얻는다. 이렇게 얻어진 신경회로망에 자연 프루닝(natural pruning) 방법을 적용하여 서로 다른 크기의 후보 신경회로망 모델을 얻는다. 이러한 학습과 복잡도 최적화의 통합 프로세스를 통하여 얻은 후보 모델들 중에서 최적의 모델을 베이시안 정보기준에 의해 선택함으로써 일반화 성능이 우수한 최적의 모델을 구성하는 방법을 제안한다. 또한 벤치마크 문제를 이용한 컴퓨터 시뮬레이션을 통하여, 제안하는 학습 및 모델 선택의 통합프로세스의 일반화 성능과 구조 최적화 성능의 우수성을 검증한다.