• Title/Summary/Keyword: K평균

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Agronomic Characteristics of Sunflower (Helianthus annuus L.) Collections (해바라기 수집종의 작물학적 특성)

  • Kim, In-Jae;Nam, Sang-Young;Lee, Yun-Ho;Kim, Seong-Jin;Choi, Seong-Yel;Rho, Chang-Woo;Lee, Jung-Gwan;Song, In-Gyu;Kim, Hong-Sig
    • Korean Journal of Plant Resources
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    • v.23 no.1
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    • pp.1-6
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    • 2010
  • To evaluate agronomic characteristics for the use of biodiesel crop, 328 collections of sunflower (Helianthus annus L.) were obtained from Genebank in Rural Development Adminstration (RDA). The necessary days from seeding to emergence of collections were from 7 to 12 days, and the days to flowering were widely distributed from 55 to 86 days. Stem length ranged from 131 to 345 cm with a mean of 259 cm, and the mean maturing days were 35 days. The number of head flower was 1~23 ea per plant, and the mean size of head flower was 17.6 cm with a range from 14.7 to 21.3 cm (72.8%). The mean seed number per head flower was 1,430 ea, and the weight of seed per plant ranged from 23 to 379 g with a mean of 91.4 g. The mean seed length was 11.7 mm with a range from 9.0 to 21.5 mm, and the mean diameter was 6.4 mm. The mean weight of seed per litter, 1000 grain weight and seed weight per plant were 322.5 g, 63.3 g and 204 g, respectively. Variation of number of head per plant was largest and weight of grain per plant was large in next among growth and grain characteristics. At the results of correlation analysis among characteristics, the seed diameter was getting bigger and the days for flowering dates were prolonged in the higher stem length plant, but the days to maturing and growth duration was shortened.

Early Osteological Development of the Larvae and Juveniles in Sebastes oblongus (Pisces: Scorpaenidae) (황점볼락(Sebastes oblongus) 자치어의 골격발달)

  • Byun, Soon-Gyu;Kang, Chung-Bae;Myoung, Jung-Goo;Cha, Ban-Seok;Han, Kyeong-Ho;Jung, Choon-Goo
    • Korean Journal of Ichthyology
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    • v.24 no.2
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    • pp.67-76
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    • 2012
  • Skeletal development in the oblong rockfish, Sebastes oblongus, was studied based on extensive larval rearing conditions from December 2007 to March 2008. Newly-hatched larvae lacked osteological elements. After 3 days of bearing, jaw bones were ossified almost simultaneously with the frontal, parietal, clavicle, opercle, preopercle and branchiostegal rays at 8.0 mm average total length (TL). Ossification of the opercular was completed by 12.3 mm and the full complement of ossified elements of cranium and pectoral girdle were completed by 16.2 mm. Ossification of the cartilaginous caudal complex began to at 9.8 mm, and completely ossified by 18.0 mm. The fusing of the first and second, and the third and fourth hypurals initially occurred by 10.8 mm, and their fusion was finally completed at 18.0 mm. Notochord flexion occurred and formed an individual centrum by 8.5 mm and 10.8 mm, respectively, and all 26 centra were ossified by 13.2 mm. The preorbital bone began to ossify on the anterior region of eye at 10.8 mm, and the $1^{st}$ suborbital bone appeared ossified on the lower of eye by 12.3 mm, and all elements were ossified at 27.5 mm. Finally, after 71 days of bearing, the juveniles became 27.5 mm, and ossification was completed at this stage.

K-Means Clustering in the PCA Subspace using an Unified Measure (통합 측도를 사용한 주성분해석 부공간에서의 k-평균 군집화 방법)

  • Yoo, Jae-Hung
    • The Journal of the Korea institute of electronic communication sciences
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    • v.17 no.4
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    • pp.703-708
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    • 2022
  • K-means clustering is a representative clustering technique. However, there is a limitation in not being able to integrate the performance evaluation scale and the method of determining the minimum number of clusters. In this paper, a method for numerically determining the minimum number of clusters is introduced. The explained variance is presented as an integrated measure. We propose that the k-means clustering method should be performed in the subspace of the PCA in order to simultaneously satisfy the minimum number of clusters and the threshold of the explained variance. It aims to present an explanation in principle why principal component analysis and k-means clustering are sequentially performed in pattern recognition and machine learning.

Visual inspection of overlapping confidence intervals for comparison of normal population means (정규 모집단의 평균 비교를 위한 신뢰구간 겹치기 시각화)

  • Choi, Sookhee;Han, Kyungsoo
    • The Korean Journal of Applied Statistics
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    • v.30 no.5
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    • pp.691-699
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    • 2017
  • Data analysts sometimes test the equality of two normal population means by the inspection of the overlapping of two confidence intervals. This method seems simple to use; however, it is a common statistical misconception to suppose that two normal means are not significantly different because of no overlapping. This article will present transforming the confidence interval of the mean difference to individual confidence intervals that are visualized to inspect overlapping. It will also be shown that this technique can be extended when comparing the k normal population means with equal variances.

A brief study on the geometric mean (기하평균에 대한 소고)

  • Yeo, In-Kwon
    • The Korean Journal of Applied Statistics
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    • v.33 no.4
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    • pp.357-364
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    • 2020
  • We review the characteristics of a geometric mean and statistical inferences based on geometric means. We also show that the statistical results obtained by the logarithmic transform and back-transformation are related to geometric means and explain how to interpret the results produced in this process.

Improving Time Efficiency of kNN Classifier Using Keywords (대표용어를 이용한 kNN 분류기의 처리속도 개선)

  • 이재윤;유수현
    • Proceedings of the Korean Society for Information Management Conference
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    • 2003.08a
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    • pp.65-72
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    • 2003
  • kNN 기법은 높은 자동분류 성능을 보여주지만 처리 속도가 느리다는 단점이 있다. 이를 극복하기 위해 입력문서의 대표용어 w개를 선정하고 이를 포함한 학습문서만으로 학습집단을 축소함으로써 자동분류 속도를 향상시키는 kw_kNN을 제안하였다. 실험 결과 대표 용어를 5개 사용할 경우에는 kNN 대비 문서간 비교횟수를 평균 18.4%로 축소할 수 있었다. 그러면서도 성능저하를 최소화하여 매크로 평균 F1 척도면에서는 차이가 없고 마이크로 평균정확률 면에서는 약 l∼2% 포인트 이내로 kNN 기법의 성능에 근접한 결과를 얻었다.

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Real-time Confidence interval estimation for Improved accuracy of Ship-inside the anomaly detection (선박내부 이상감지의 정확도 향상을 위한 실시간 신뢰구간 추정)

  • Kim, Yeong-Ju;Heo, yu Kyung;Jeong, Majung-A
    • Proceedings of the Korea Information Processing Society Conference
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    • 2014.04a
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    • pp.721-723
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    • 2014
  • 본 논문은 선박내부의 센서데이터 이상감지를 위해 실시간 신뢰구간을 설정하고 신뢰구간을 초과하거나 미만이 되면 경보를 통해 관리자에게 알려주는 모니터링을 위한 신뢰구간 추정이다. 여기서, 이상 감지 예측의 정확도 향상을 위해 단순지수평활법과 이동평균법의 평균제곱오차를 비교 평가 하였다. 실험결과, 이동평균법의 평균제곱오차가 단순지수평활법 보다 적게 나와 선박 내부 모니터링을 위한 신뢰구간은 이동평균법을 적용하였다.

Effects of Conductivity and Thickness on Natural Convection Heat Transfer From a Horizontal Circular Tube (수평 원통관의 열전도율과 두께가 자연대류 열전달에 미치는 영향)

  • 정영식;강병희;권순석
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.10 no.2
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    • pp.265-279
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    • 1986
  • Ra=$10^{6}$, Pr=5에서 관열전도율과 두께가 변화할 때의 단일수평관에서의 자연대류 열전달에 관하여 유한차분법을 이용하여 해석적으로 연구하였다. .delta.$_{w}$ /d$_{o}$ =0.1에서 관열전도율이 높을수록 높은 온도와 높은 국소 누셀트 수를 나타 내며, .theta.=20。에서의 원주방향속도는 (r-r$_{o}$ )=0.08에서 최대가 되며 반경방향속 도는 (r-r$_{o}$ )=0.14에서 최대가 된다. 관외벽온도는 관 두께가 증가함에 따라 거의 유사하게 감소한다. $K_{w}$ /K$_{f}$ =75에서 각도변위가 증가함게 따라 국소 누셀트수는 현저히 증가하나 관 두께가 증가함에 따라서는 감소한다. .delta.$_{w}$ / d$_{o}$ =0.1에서 평균 누셀트수와 평균 온도는 무차원 열전도율이 증가함에 따라 $K_{w}$ /K$_{f}$ >15에서는 평균 누셀트 수는 서서히 증가하고 평균 온도는 거의 같 은 값을 가지며 지수함수로 표시할 수 있었다. $K_{w}$ /K$_{f}$ =75,50에서 평균 누 셀트수와 온도는 무차원 관 두께가 증가함에 따라 거의 직선적으로 감소되며 선형 함 수로 나타낼 수 있었다.

Water Requirement of Potato According to Growth Stage (노지재배 감자의 생육시기별 물 요구량 구명)

  • Eom, Ki-Cheol;Park, So-Hyun;Yoo, Sung-Yung
    • Korean Journal of Soil Science and Fertilizer
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    • v.45 no.6
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    • pp.861-866
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    • 2012
  • Water is the most important resource for the potato cultivation, especially to get the maximum water use efficiency and yield of potato, Water has to be applied moderately based on the water requirement of the potato. Crop water requirement (WR) is a function of the Potential evapo-transpiration(PET) and Crop coefficient (Kc). PET can be estimated by the climate data measured at the weather station in the production region. Kc was measured by the NIAST (RDA) through Lysimeter experiments. In this study, the growth stage of potato was divided as four (G-1 : Apr. 1~Apr. 15, G-2 : Apr. 16~May. 10, G-3 : May. 11~May. 31, G4 : Jun. 1~Jun. 15). The average PET during potato growing season of the 45 areas was $2.95mm\;day^{-1}$. The most water requirement was the G-3 stage among the potato growth stage. The MWR (Mean water requirement) according to growth stage was 1.0~1.2 (average 1.1), 1.5~1.8 (average 1.6), 1.9~2.2 (average 2.0) and 1.7~2.1 (average 1.8) mm $day^{-1}$, in the G-1, G-2, G-3 and G-4 stage, respectively. The TWR (Total water requirement) according to growth stage was 18.0~22.1 (average 19.3), 50.6~66.6 (average 56.3), 63.5~88.2 (average 72.4) and 38.3~54.5 (average 44) mm, in the G-1, G-2, G-3 and G-4 stage, respectively.

Comparison of Accuracy for Chromosome Classification using Different Feature Extraction Methods based on Density Profile (Density Profile 추출 방법에 따른 염색체 분류정확도 비교분석)

  • Choi, Kwang-Won;Song, Hae-Jung;Kim, Jong-Dae;Kim, Yu-Seop;Lee, Wan-Yeon;Park, Chan-Young
    • Proceedings of the Korean Information Science Society Conference
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    • 2010.06c
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    • pp.226-229
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    • 2010
  • 본 연구에서는 다양한 density profile 특징추출에 기반한 염색체 자동분류방법들의 성능을 비교분석하였다. density profile은 염색체의 밴드패턴을 가장 잘 표현한 특징으로 염색체의 중심축을 구성하는 화소들의 밝기 값을 추출하는 방법이다. 염색체의 밴드패턴은 염색체의 끝단까지를 잘 표현해주어야만 정확한 염색체번호를 확인할 수 있다. 따라서 염색체의 중심축을 추출하여 염색체 끝단까지 확장 처리한 방법에 대한 성능을 확인하였다. 염색체 중심축에 위치한 화소만을 이용한 프로파일은 잡음에 민감할 수 있으므로 이를 해결하기 위하여 염색체의 중심축에 대한 화소 값 대신 주변 밝기 값들에 대한 평균을 이용한 국소평균방법과 중심축의 수직라인 상에 존재하는 화소 값들에 대한 평균을 구한 수직평균방법을 비교하였다. 분류알고리즘은 k-NN을 사용하였고, 실험데이터는 (주)Gendix 로부터 제공받은 임상적으로 정상인 100명(남자 50명, 여자 50명)으로부터 추출한 4600개의 염색체 영상을 훈련데이터와 테스트데이터로 각각 50%씩 랜덤하게 분리하여 실험하였다. 실험결과 중심축을 확장하고 수직평균에 대한 프로파일을 특징으로 추출하여 분류한 경우가 가장 좋은 성능을 보였다.

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