Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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This study was aimed at identifying the ecotype Apis mellifera subspecies in the savannah vegetation zone of Nigeria based on wing morphology and landmarks variations of samples collected from five States of savannah agroecological zone in the country. The measured variables were subjected to analysis with parametric statistic tools of mean, standard deviation and standard error. The distribution and relation between them were subjected to two step cluster analysis. Morphoclusters means were presented in centroids and also the simultaneous confidence intervals (95%) of means values of wing morphometric and landmarks were expressed. Savannah vegetation honeybee samples were classified into two distinct morphoclusters. Morphoclusters 1 constituted 56.4% of honeybees in the region while morphoclusters 2 had 43.6%. The within cluster percentage of state of honeybee showed all honeybee samples collected from Kebbi (100%) State were of morphoclusters 1 and also, morphoclusters 2 in Kaduna (100%) and Kwara (100%)States.
Dr. Oyerinde. 2012. \u201cMorphometric and Landmark Based Variations of Apis mellifera L. Wings in the Savannah Agro-ecological Zone of Nigeria\u201d. Global Journal of Science Frontier Research - D: Agriculture & Veterinary GJSFR-D Volume 12 (GJSFR Volume 12 Issue D7): .
Crossref Journal DOI 10.17406/GJSFR
Print ISSN 0975-5896
e-ISSN 2249-4626
The methods for personal identification and authentication are no exception.
Total Score: 115
Country: Nigeria
Subject: Global Journal of Science Frontier Research - D: Agriculture & Veterinary
Authors: Dr. Oyerinde, A. A., Dike, M. C. , Banwo, O. O. , Bamaiyi, L. J., Adamu, R. S. (PhD/Dr. count: 1)
View Count (all-time): 177
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Publish Date: 2012 08, Fri
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This study was aimed at identifying the ecotype Apis mellifera subspecies in the savannah vegetation zone of Nigeria based on wing morphology and landmarks variations of samples collected from five States of savannah agroecological zone in the country. The measured variables were subjected to analysis with parametric statistic tools of mean, standard deviation and standard error. The distribution and relation between them were subjected to two step cluster analysis. Morphoclusters means were presented in centroids and also the simultaneous confidence intervals (95%) of means values of wing morphometric and landmarks were expressed. Savannah vegetation honeybee samples were classified into two distinct morphoclusters. Morphoclusters 1 constituted 56.4% of honeybees in the region while morphoclusters 2 had 43.6%. The within cluster percentage of state of honeybee showed all honeybee samples collected from Kebbi (100%) State were of morphoclusters 1 and also, morphoclusters 2 in Kaduna (100%) and Kwara (100%)States.
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