Determination of morphological variability of different pisum genotypes using principal component analysis
نویسندگان
چکیده
منابع مشابه
development of different optical methods for determination of glucose using cadmium telluride quantum dots and silver nanoparticles
a simple, rapid and low-cost scanner spectroscopy method for the glucose determination by utilizing glucose oxidase and cdte/tga quantum dots as chromoionophore has been described. the detection was based on the combination of the glucose enzymatic reaction and the quenching effect of h2o2 on the cdte quantum dots (qds) photoluminescence.in this study glucose was determined by utilizing glucose...
An assessment of the anatomical variability and contributing factors of female pelvis shape using principal component analysis
Background & aim: Pelvic shape has important effects on obstetrical outcomes. Therefore, this study aimed to determine the etiologic factors that contribute to the formation of female pelvis and describe its variability. Methods: This study was conducted on 131 women referring to Saint Joseph Hospital, Marseille...
متن کاملanalysis of ruin probability for insurance companies using markov chain
در این پایان نامه نشان داده ایم که چگونه می توان مدل ریسک بیمه ای اسپیرر اندرسون را به کمک زنجیره های مارکوف تعریف کرد. سپس به کمک روش های آنالیز ماتریسی احتمال برشکستگی ، میزان مازاد در هنگام برشکستگی و میزان کسری بودجه در زمان وقوع برشکستگی را محاسبه کرده ایم. هدف ما در این پایان نامه بسیار محاسباتی و کاربردی تر از روش های است که در گذشته برای محاسبه این احتمال ارائه شده است. در ابتدا ما نشا...
15 صفحه اولAssessing Atmospheric Variability using Kernel Principal Component Analysis
A popular methodology to filter seemingly chaotic atmospheric flow into an ordered set of modes of variability is to identify those patterns of geopotential height that occur often. Historically, understanding of the leading patterns or modes of variability was determined through linear statistical methods. Recently, nonlinear methods, such as kernel principal component analysis (KPCA), have be...
متن کاملCompression of Breast Cancer Images By Principal Component Analysis
The principle of dimensionality reduction with PCA is the representation of the dataset ‘X’in terms of eigenvectors ei ∈ RN of its covariance matrix. The eigenvectors oriented in the direction with the maximum variance of X in RN carry the most relevant information of X. These eigenvectors are called principal components [8]. Ass...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: LEGUME RESEARCH - AN INTERNATIONAL JOURNAL
سال: 2018
ISSN: 0976-0571,0250-5371
DOI: 10.18805/lr-438