• Title/Summary/Keyword: principal period-2 component

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A Construction of the Principal Period-2 Component in the Degree-9 Bifurcation Set with Parametric Boundaries (9차 분기집합의 2-주기 성분의 경계방정식에 관한 연구)

  • Geum, Young-Bee
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.7 no.6
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    • pp.1421-1424
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    • 2006
  • By extending the Mandelbrot set for the complex polynomial $$M={c\in C\;:\; _{k\rightarrow\infty}^{lim}P_c^k(0)\;{\neq}\;{\infty}$$ we define the degree-n bifurcation set. In this paper, we formulate the boundary equation of a period-2 component on the main component in the degree-9 bifurcation set by parameterizing its image. We establish an algorithm constructing a period-2 component in the degree-9 bifurcation set and the typical implementations show the satisfactory result with Mathematica codes grounded on the analysis.

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Assessment and Classification of Korean Indigenous Corn Lines by Application of Principal Component Analysis (주성분분석에 의한 재래종 옥수수의 해석)

  • 이인섭;박종옥
    • Journal of Life Science
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    • v.13 no.3
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    • pp.343-348
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    • 2003
  • This study was conducted to get basic information on the Korean local corn line collected from Busan City and Kyungnam Province, a total of 49 lines were selected and assessed by the principal component analysis method. In the result of principal component analysis for 7 characteristics, 67.4% and 86.3% of total variation could be appreciated by the first two and first four principal components, respectively. Contribution of characteristics to principal component was high at upper principal components and low at lower principal components. Biological meaning of principal component and plant types corresponding to the each principal component were explained clearly by the correlation coefficient between principal component and characteristics. The first principal component appeared to correspond to the size of plant and ear, and the duration of vegetative growing period. The second principal component appeared to correspond to the number of ear and tiller. But the meaning of the third and fourth principal components were not clear.

A Study on the Characteristics of Concentrations of Atmospheric Aerosols in Pusan (부산지역의 입자상 대기오염물질의 농도특성에 관한 연구)

  • 최금찬;유수영;전보경
    • Journal of Environmental Health Sciences
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    • v.26 no.2
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    • pp.41-48
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    • 2000
  • This study has been carried out to determine the seasonal characteristics of concentration of various ionic (CI-, NO3-, SO42-, Na+, NH+, K+, Ca2+) and heavy metallic (Pb, Mn, Cu, Ni) species in Pusan from August 1997 to April 1998. The concentrations of CI-, Na+, K+ were higher during summer with 2.98 ${\mu}{\textrm}{m}$/㎥. Seasonal variation of total concentration of but the concentration of NH4+ was higher during winter with 2.46${\mu}{\textrm}{m}$/㎥. Seasonal variation of total concentration of heavy metals(Pb, Cu, Mn, Ni) were 186.0 ng/㎥ in summer, 222.6 ng/㎥ in autumn, and 135.83 ng/㎥ in winter. Over the seasons inspected, the concentration of Mn was higher in coarse particles than fine particles and concentration of Ni was higher in fine particles than coarse particles. during yellow sand period, the concentration of TSP was increased about two times than that of other period. SO42-, Ca2+ concentrations were higher than other ionic components because of soil particles. The concentration of Ni showed 94.62ng/㎥ was increased about 4~5 times than other period. Principal component of the yellow sand, SO42-, Ca2+ could be discreased by rainfall and washout effect of atmospheric aerosol was higher in coarse particles than fine particles. Results from PCA(principal component analysis) showed that major pollutant was NaCl by seasalt particulate and (NH4)2SO4.

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A Study on the Body Type of Hanwoo(Korean Cattle) Steer by Using Principal Components Analysis (주성분 분석을 이용한 거세한우의 체형분류에 관한 연구)

  • Ha, D.W.;Kim, H.C.;Kim, B.W.;Lee, M.Y.;Lee, J.H.;Shin, C.K.;Do, C.H.;Lee, J.G.
    • Journal of Animal Science and Technology
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    • v.44 no.6
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    • pp.643-652
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    • 2002
  • Data were consisted of the ten body measurements (withers height, rump height, body length, chest depth, chest width, rump width, rump length, thurls width, hipbone width and chest girth) of 642 steers (Korean cattle), which was entered in the National Beef Quality Contest hosted by the Korea Animal Improvement Association from 1997 to 2001. A principal components analysis was used to classify the body types of the steers, and estimate the correlations between carcass traits and principal components for the body measurements of the first, second, third and fourth period, respectively. The first principal component of body measurements at the first, second, third and fourth period accounted for 76.0%, 83.0%, 72.7% and 57.4% of the total variance, respectively. The sum of first, second and third principal component at each period accounted for 86.69%, 90.49%, 84.62% and 77.26% of the total variance, respectively. At each period, all the first principal component of the body measurements were positive and it generally showed large framed body shape. The size of body was influenced mostly by chest depth(0.328${\sim}$0.339) and rump length(0.325${\sim}$0.341). The second, third and fourth principal component at the each period were various. There were positive correlations between principal components index of each period and carcass traits such as carcass weight(0.539${\sim}$0.755), average daily gain(0.256${\sim}$0.564), backfat thickness(0.227${\sim}$0.280), and eye muscle area(0.187${\sim}$0.344). The correlation with yield grade index(-0.246${\sim}$-0.110), however, was negative. The correlation with marbling score(0.066${\sim}$0.099) was low or statistically insignificant. According to principal component indexes of the second, third, and fourth components, the correlations with the carcass traits were various. There were no large differences between the correlations of the single body measurement trait with the carcass traits and the correlations of the first principal component indexes with the carcass traits.

Comparison of Dietary Externalization in Korea and Japan -by Principal Component Analysis- (식생활 외부화에 관한 한일 비교 연구 -주성분 분석을 이용하여-)

  • Choi Hyun-Sook
    • Journal of the East Asian Society of Dietary Life
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    • v.16 no.1
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    • pp.23-28
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    • 2006
  • The purpose of this paper was to clarify the actual conditions of the 'Dietary externalization' mainly by using the economic and nutrition-related data, accompanied by the economic development in Korea and Japan. 'Modernization of food style' and other modernization have taken place, among which 'Dietary externalization' in particular has recently drawn interest. At the time this paper clarified with econometric analysis whether there are differences between the two countries in term of the modernization of food style and dietary externalization trend. The trends of Dietary externalization of both Korea and Japan were studied using Principal Component Analysis method. The food subgroup were investigated based on the annual report on the household income and expenditure survey of Korea and the annual report on the family income and expenditure survey of Japan. The statistical data from both country were analyzed by SAS program. The results are as follows; 1. In Korea, the ratio of carbohydrates in the total calorie intake is quite high and animal protein is rather low compared to those in Japan. 2. Traditional food such as grains and vegetables are consumed much more in Korea than in Japan. 3. The Principal Component 1, 2 were extracted in both countries during the whole analysis period, which suggested the 'Dietary externalization' 4. Principal Component 1 has a positive factor loaded in all food items including meals outside the home and process food. In other words, it is apparent that the 'Dietary externalization' tread in Korea has a simple pattern suggesting that all externalization related items are on the rise. 5. Principal component 1, 2 which indicated the dietary externalization, were detected in Japan.

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Assessment of water quality variations under non-rainy and rainy conditions by principal component analysis techniques in Lake Doam watershed, Korea

  • Bhattrai, Bal Dev;Kwak, Sungjin;Heo, Woomyung
    • Journal of Ecology and Environment
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    • v.38 no.2
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    • pp.145-156
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    • 2015
  • This study was based on water quality data of the Lake Doam watershed, monitored from 2010 to 2013 at eight different sites with multiple physiochemical parameters. The dataset was divided into two sub-datasets, namely, non-rainy and rainy. Principal component analysis (PCA) and factor analysis (FA) techniques were applied to evaluate seasonal correlations of water quality parameters and extract the most significant parameters influencing stream water quality. The first five principal components identified by PCA techniques explained greater than 80% of the total variance for both datasets. PCA and FA results indicated that total nitrogen, nitrate nitrogen, total phosphorus, and dissolved inorganic phosphorus were the most significant parameters under the non-rainy condition. This indicates that organic and inorganic pollutants loads in the streams can be related to discharges from point sources (domestic discharges) and non-point sources (agriculture, forest) of pollution. During the rainy period, turbidity, suspended solids, nitrate nitrogen, and dissolved inorganic phosphorus were identified as the most significant parameters. Physical parameters, suspended solids, and turbidity, are related to soil erosion and runoff from the basin. Organic and inorganic pollutants during the rainy period can be linked to decayed matters, manure, and inorganic fertilizers used in farming. Thus, the results of this study suggest that principal component analysis techniques are useful for analysis and interpretation of data and identification of pollution factors, which are valuable for understanding seasonal variations in water quality for effective management.

AN EFFICIENT CONSTRUCTION OF PERIOD-2 BULBS IN THE CUBIC MANDELBROT SET WITH PARAMETRIC BOUNDARIES

  • Geum, Young-Hee;Kim, Young-Ik;Lee, Kang-Sup
    • Journal of applied mathematics & informatics
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    • v.25 no.1_2
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    • pp.109-118
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    • 2007
  • A parametric boundary equation is established for the principal period-2 bulb in the cubic Mandelbrot set. Using its geometry, an efficient escape-time algorithm which reduces the construction time for the period-2 bulbs in the cubic Mandelbrot set is introduced and the implementation graphic results display the fascinating fractal beauty.

Prediction of the $24^{th}$ Solar Maximum Based on the Principal Component-and-Autoregression method

  • Chae, Jong-Chul;Oh, Seung-Jun
    • The Bulletin of The Korean Astronomical Society
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    • v.36 no.2
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    • pp.100.1-100.1
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    • 2011
  • Everybody wants to see the future, but nobody does for sure. Reliably forecasting the solar activity in the near future looks like an easy task, but in fact still remains one of difficult problems in the solar-terrestrial research. We have sought for good univariate methods that can predict future smoothed sunspot numbers reasonably well based on past smoothed sunspot number data only. Here we consider a specific method we call principal component-and-autoregression (PCAR) method. The variation of sunspot number during a period of finite duration (past) before an epoch (present) is modeled by a linear combination of a small number of dominant principal components, and this model is extended to the period (future) beyond the epoch using the autoregressive model of finite order. From the application of this method, we find that the $24^{th}$ solar maximum is likely to occur near the end of the year 2013 (and there is a possibility that it occurs earlier near the start of 2013), and to have a peak sunspot number of about 86, indicating that the activity of the $24^{th}$ cycle will be weaker than the average. We will discuss how much this estimate is reliable.

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Study on the applicability of the principal component analysis for detecting leaks in water pipe networks (상수관망의 누수감지를 위한 주성분 분석의 적용 가능성에 대한 연구)

  • Kim, Kimin;Park, Suwan
    • Journal of Korean Society of Water and Wastewater
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    • v.33 no.2
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    • pp.159-167
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    • 2019
  • In this paper the potential of the principal component analysis(PCA) technique for the application of detecting leaks in water pipe networks was evaluated. For this purpose the PCA was conducted to evaluate the relevance of the calculated outliers of a PCA model utilizing the recorded pipe flows and the recorded pipe leak incidents of a case study water distribution system. The PCA technique was enhanced by applying the computational algorithms developed in this study which were designed to extract a partial set of flow data from the original 24 hour flow data so that the effective outlier detection rate was maximized. The relevance of the calculated outliers of a PCA model and the recorded pipe leak incidents was analyzed. The developed algorithm may be applied in determining further leak detection field work for water distribution blocks that have more than 70% of the effective outlier detection rate. However, the analysis suggested that further development on the algorithm is needed to enhance the applicability of the PCA in detecting leaks by considering series of leak reports happening in a relatively short period.

Classification and Selection of the Breeding materials in the Silkworm, Bombyx mori, by Multivariate Analysis 1. Classification of the Silkworm Genetic Stocks by Principal Component Analysis and Cluster Analysis (다변량 해석법에 의한 누에 육종소재의 탐색 1. 주성분분석과 집락분석을 이용한 누에품종분류)

  • 정도섭;이인정
    • Journal of Sericultural and Entomological Science
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    • v.31 no.2
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    • pp.102-112
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    • 1989
  • Principal component analysis and cluster analysis were performed on the nine quantitative characters of the one hundred and forty eight silkworm genetic stocks. The six major quantitative characters such as cocoon yield, cocoon weight, cocoon shell weight, cocoon shell percentage, larval period of the 5th instar silkworm, and total larval period showed significantly positive correlation between them. The first three principal components extracted form the initial nine variables by principal component analysis accounted for about eighty percent of original information. The first and second principal components were characterized as factors related to silk productivity, and cocoon productivity, respectively. On the basis of multivariate analysis using city block distance determined from the first three principal components to measure the phenotypic diversity, the one hundred and forty eight silkworm genetic stocks could be clustered into seven varietal groups, and the phenotypic diversity between the varietal groups was partly related to their geographical origins. Among 7 varietal group, group II and IV revealed higher silk and cocoon productivity.

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