by K. Prudhvi
Original Research
In this paper, we obtain coincidence points and common fixed point theorem for four self-mappings via weakly compatible mappings in cone metric spaces, where the cone is not necessarily normal. These results are improved and generalized several well- known comparable results existing in the references.
American Journal of Applied Mathematics and Statistics. 2017, 5(3), 112-114. DOI: 10.12691/ajams-5-3-5
Pub. Date: September 07, 2017
8421 Views2651 Downloads
by Haiwu Huang, Xiongtao Wu and Yanchun Yi
Original Research
In this work, the complete moment convergence and Lpconvergence for asymptotically almost negatively associated (AANA, in short) random variables are investigated. As an application, the complete convergence theorem for weighted sums of AANA random variables is obtained. These theorems obtained extend and improve some earlier results.
American Journal of Applied Mathematics and Statistics. 2017, 5(3), 106-111. DOI: 10.12691/ajams-5-3-4
Pub. Date: September 05, 2017
8173 Views1928 Downloads
by Bumjun Park
Original Research
The 2016 Presidential Election was an international surprise, as President Donald Trump came back from a seemingly large deficit in the pre-election opinion polls. As most, if not all, of the major polls missed the election results, the public started to doubt the credibility of pre-election polls. This article proposes that there was a methodological error in the polls. The polls used the census data of American population to weigh their data. However, population may not have a correlation with turnout, meaning that a certain population group may not vote much; not contributing to the electorate. For this reason, the polls based on population might systematically over or underestimate a particular candidate. Thereby, the proposition is that the polling agencies should consider the electorate, not the population for modifying the polling results. The proposition is substantiated with a series of statistical simulations supporting the claim that a poll conducted based on the electorate resembles the actual result more accurately. Conclusively, it argues that, as the polls play a pivotal role in affecting the media and the electorate, the improvement of polls is necessary for well-informed forecasts to be available.
American Journal of Applied Mathematics and Statistics. 2017, 5(3), 101-105. DOI: 10.12691/ajams-5-3-3
Pub. Date: August 20, 2017
11953 Views2328 Downloads
by Michael Gr. Voskoglou
Review Article
The effectiveness of mathematics in the natural sciences was characterized by the famous Nobel prize holder E. P. Winger as being unreasonable. It is not difficult for one to understand that this characterization is related to a question that has occupied the interest of philosophers, mathematicians and other scientists at least from the Plato’s era in ancient , until today: “Is mathematics discovered or invented by humans”? In the present work in an effort to obtain a convincing explanation of the above Winger’s “enigma”, the existing philosophical views about the above question are critically examined and discussed in connection with the advances in the history of mathematics that affected the human beliefs about them.
American Journal of Applied Mathematics and Statistics. 2017, 5(3), 95-100. DOI: 10.12691/ajams-5-3-2
Pub. Date: August 07, 2017
9875 Views2288 Downloads
by Eman A. Abo Elfadl and Fatma D. M. Abdallah
Original Research
Background & objectives: This study was undertaken to compare the accuracies of Discriminant analysis model (DA) and Artificial neural networks model (ANN) for classification and prediction of Friesian cattle fertility status by using its reproductive traits.Methods: Data was collected through field survey of 2843 animal records of Friesian breed belongs to El Dakhalia province farms, Egypt. Data was covering the period extended from 2010 to 2013. The samples of dairy production sectors were selected randomly. Data was collected from valid farm records or the structured questionnaires established by the researcher. Results: The results of classification accuracy indicated that the artificial neural network (ANN) model is more efficient than the discriminant analysis (DA) model in expressing overall classification accuracy and accuracies of correctly classified cases of fertility status for Friesian cattle. The results showed that The ANN models had shown the highest classification accuracy (93.6%) for year (2010) while, it was (79.9%) for DA. The comparison of overall classification accuracies clearly favored the supremacy of ANN over DA. The results also were confirmed by the areas under Receiver Operating Characteristic Curves (ROC) captured by ANN and DA. ROC curves are used mainly for comparing different discriminating rates. Areas under ROC curves were higher in case of ANN models across the different years compared to DA models. The differences in accuracies were also significant at 5% level of significance with p-value 0.005 by using Paired Sample t-test. From all of the above we can conclude that artificial neural network model was more accurate in prediction and classification of fertility status than a traditional statistical model (Discriminant analysis).
American Journal of Applied Mathematics and Statistics. 2017, 5(3), 90-94. DOI: 10.12691/ajams-5-3-1
Pub. Date: August 05, 2017
11664 Views3129 Downloads1 Likes