Allozyme variation of old Ginkgobiloba memorial trees in western Japan

1992 ◽  
Vol 22 (7) ◽  
pp. 939-944 ◽  
Author(s):  
Yoshihiko Tsumura ◽  
Hiroshi Motoike ◽  
Kihachiro Ohba
Keyword(s):  
Principal Component Analysis ◽  
Discriminant Analysis ◽  
Genetic Relationships ◽  
Principal Component ◽  
Allozyme Variation ◽  
Canonical Discriminant Analysis ◽  
Scatter Diagram ◽  
Enzyme Systems ◽  
Multivariate Procedures ◽  
Western Japan

Allozyme variation of 89 old memorial trees of Ginkgobiloba L. in western Japan were investigated. For 12 loci from 10 enzyme systems, the percentage of polymorphic loci (95% level), the number of alleles per locus, and the observed heterozygosity were 75.0%, 2.5, and 0.234, respectively. The variation of this species is relatively high in comparison with other gymnosperms. Genetic relationships between four regions (Kansai, Shikoku, North Kyushu, and South Kyushu) were investigated by using two multivariate procedures. Based on a principal component analysis, these four regional groups were not separated clearly, except for the Shikoku and South Kyushu groups, which were almost completely separated in opposite peripheral zones of a scatter diagram. The canonical discriminant analysis also almost completely separated the Shikoku and South Kyushu groups. These results indicate that most trees of the Shikoku and South Kyushu groups might be descendants of individuals from the Kansai and North Kyushu groups, respectively, excluding some exceptions.

scholarly journals Combined approach based on principal component analysis and canonical discriminant analysis for investigating hyperspectral plant response

2012 ◽  
Vol 7 (3) ◽  
pp. 34 ◽  
Author(s):  
Anna Maria Stellacci ◽  
Annamaria Castrignanò ◽  
Mariangela Diacono ◽  
Antonio Troccoli ◽  
Adelaide Ciccarese ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Discriminant Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Canonical Discriminant Analysis ◽  
Plant Response ◽  
Combined Approach

scholarly journals Comparative analysis of populations of the Balkan endemic species Daphne malyana Blecic (Thymeleaceae)

2010 ◽  
Vol 62 (4) ◽  
pp. 1151-1162 ◽  
Author(s):  
Marina Juskovic ◽  
P. Vasiljevic ◽  
V. Randjelovic ◽  
V. Stevanovic ◽  
Branka Stevanovic
Keyword(s):  
Principal Component Analysis ◽  
Comparative Analysis ◽  
Endemic Species ◽  
Morphological Variability ◽  
Principal Component ◽  
Balkan Peninsula ◽  
Canonical Discriminant Analysis ◽  
The Other ◽  
Isolated Populations ◽  
Microclimate Conditions

Daphne malyana Blecic (Thymeleaceae) is an endemic species of the western part of the Balkan Peninsula, distributed in the mountains, canyons and gorges of N. Montenegro, E. Bosnia and W. Serbia. The comparative morphoanatomic investigations have included four distantly separated populations of the species D. malyana, i.e. two from Serbia, from the ravines of Sokoline and Vranjak on Mt. Tara, and two from Montenegro, in the canyons of the Tara and Piva rivers. Comparative morphoanatomical studies have shown the presence of general adaptive characteristics of a specific, conservative xeromorphic type, slightly differing in each population. Principal component analysis (PCA) and canonical discriminant analysis (CDA) of 20 morphoanatomical characteristics of the leaves and stems have shown a clear distinction between the populations from the river Piva canyon (Montenegro) and those from the Sokoline ravine (Serbia), on one side, and those of Vranjak gorge (Serbia) and of the river Tara canyon (Montenegro) on the other side. It may be assumed that the mild morphological variability of the isolated populations of the Balkan endemic species D. malyana in the canyons and gorges seem to have been affected by the microclimate conditions in their habitats.

scholarly journals Analisis Metode Pengenalan Wajah Two Dimensial Principal Component Analysis (2DPCA) dan Kernel Fisher Discriminant Analysis Menggunakan Klasifikasi KNN (K- Nearest Neighbor)

2020 ◽  
Vol 2 (2) ◽  
pp. 29-38
Author(s):  
Abdur Rohman Harits Martawireja ◽  
Hilman Mujahid Purnama ◽  
Atika Nur Rahmawati
Keyword(s):  
Principal Component Analysis ◽  
Discriminant Analysis ◽  
Cross Validation ◽  
Nearest Neighbor ◽  
Principal Component ◽  
Component Analysis ◽  
K Nearest Neighbor ◽  
Fisher Discriminant Analysis ◽  
Fisher Discriminant ◽  
Kernel Fisher Discriminant Analysis

Pengenalan wajah manusia (face recognition) merupakan salah satu bidang penelitian yang penting dan belakangan ini banyak aplikasi yang menerapkannya, baik di bidang komersil ataupun di bidang penegakan hukum. Pengenalan wajah merupakan sebuah sistem yang berfungsikan untuk mengidentifikasi berdasarkan ciri-ciri dari wajah seseorang berbasis biometrik yang memiliki keakuratan tinggi. Pengenalan wajah dapat diterapkan pada sistem keamanan. Banyak metode yang dapat digunakan dalam aplikasi pengenalan wajah untuk keamanan sistem, namun pada artikel ini akan membahas tentang dua metode yaitu Two Dimensial Principal Component Analysis dan Kernel Fisher Discriminant Analysis dengan metode klasifikasi menggunakan K-Nearest Neigbor. Kedua metode ini diuji menggunakan metode cross validation. Hasil dari penelitian terdahulu terbukti bahwa sistem pengenalan wajah metode Two Dimensial Principal Component Analysis dengan 5-folds cross validation menghasilkan akurasi sebesar 88,73%, sedangkan dengan 2-folds validation akurasi yang dihasilkan sebesar 89,25%. Dan pengujian metode Kernel Fisher Discriminant dengan 2-folds cross validation menghasilkan akurasi rata rata sebesar 83,10%.

2D Image Matrix-Based Discriminator

2006 ◽  
pp. 258-286
Author(s):  
David Zhang ◽  
Xiao-Yuan Jing ◽  
Jian Yang
Keyword(s):  
Principal Component Analysis ◽  
Discriminant Analysis ◽  
Linear Discriminant Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Two Dimensional ◽  
Fisher Linear Discriminant ◽  
Linear Discriminant ◽  
Image Projection ◽  
Projection Techniques

This chapter presents two straightforward image projection techniques — two-dimensional (2D) image matrix-based principal component analysis (IMPCA, 2DPCA) and 2D image matrix-based Fisher linear discriminant analysis (IMLDA, 2DLDA). After a brief introduction, we first introduce IMPCA. Then IMLDA technology is given. As a result, we summarize some useful conclusions.

scholarly journals Development of a Piezoelectric-Based Odor Reproduction System

Electronics ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 870
Author(s):  
Tengteng Wen ◽  
Dehan Luo ◽  
Yongjie Ji ◽  
Pingzhong Zhong
Keyword(s):  
Principal Component Analysis ◽  
Discriminant Analysis ◽  
Linear Discriminant Analysis ◽  
Electronic Nose ◽  
Principal Component ◽  
Component Analysis ◽  
Piezoelectric Transducers ◽  
Linear Discriminant ◽  
Reproduction System ◽  
Machine Olfaction

Odor reproduction, a branch of machine olfaction, is a technology through which a machine represents various odors by blending several odor sources in different proportions and releases them. In this paper, an odor reproduction system is proposed. The system includes an atomization-based odor dispenser using 16 micro-porous piezoelectric transducers. The authors propose the use of an electronic nose combined with a Principal Component Analysis–Linear Discriminant Analysis (PCA–LDA) model to evaluate the effectiveness of the system. The results indicate that the model can be used to evaluate the system.

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