The Wiener, Eccentric Connectivity and Zagreb Indices of the Hierarchical Product of Graphs

Let G1 = (V1, E1) and G2 = (V2, E2) be two graphs having a distinguished or root vertex, labeled 0. The hierarchical product G2 ⊓ G1 of G2 and G1 is a graph with vertex set V2 × V1. Two vertices y2y1 and x2x1 are adjacent if and only if y1x1 ∈ E1 and y2 = x2; or y2x2 ∈ E2 and y1 = x1 = 0. In this paper, the Wiener, eccentric connectivity and Zagreb indices of this new operation of graphs are computed. As an application, these topological indices for a class of alkanes are computed. ACM Computing Classification System (1998): G.2.2, G.2.3.The research of this paper is partially supported by the University of Kashan under grant no 159020/12

Using Machine Learning for Land Suitability Classification

Artificial intelligence and machine learning methods can be used to automate the land suitability classification. Multiple Classifier System (MCS) or ensemble methods are rapidly growing and receiving a lot of attention and proved to be more accurate and robust than an excellent single classifier in many fields. In this study a dataset based land suitability classification is addressed. It is done using a newly proposed ensemble classifier generation technique referred to as RotBoost, which is constructed by combining Rotation Forest and AdaBoost, and it is known to be the first time that RotBoost has been applied for suitability classification. The experiments conducted with the study area, Shavur plain, lies in the northern of Khuzestan province, southwest of Iran. It should be noted that suitability classes for the input data were calculated according to FAO method. This provides positive evidence for the utility of machine learning methods in land suitability classification especially MCS methods. The results demonstrate that RotBoost can generate ensemble classifiers with significantly higher prediction accuracy than either Rotation Forest or AdaBoost, which is about 99% and 88.5%, using two different performance evaluation measures

Effects of Rejuvenators on High-RAP Mixtures Based on Laboratory Tests of Asphalt Concrete Mixtures and Fine Aggregate Matrix Mixtures

Although the linear viscoelastic stiffness, fracture characteristics, and permanent deformation behavior of AC mixtures can be determined through experiments, it is generally time-consuming and expensive to reach statistically repeatable results. Thus, it is attractive to pursue alternative methods that are cheaper, faster, and repeatable in order to efficiently evaluate and predict asphalt mixtures’ core mechanical characteristics (such as stiffness, fatigue, and plastic deformation)

Global analysis of nuclear parton distribution functions and their uncertainties at next-to-next-to-leading order

We perform a next-to-next-to-leading order (NNLO) analysis of nuclear parton distribution functions (nPDFs) using neutral current charged-lepton (ℓ±+nucleus) deeply inelastic scattering (DIS) data and Drell-Yan (DY) cross-section ratios σADY/σA′DY for several nuclear targets. We study in detail the parametrizations and the atomic mass (A) dependence of the nuclear PDFs at this order. The present nuclear PDFs global analysis provides us a complete set of nuclear PDFs, f (A,Z)i(x,Q2) , with a full functional dependence on x , A, Q 2 . The uncertainties of the obtained nuclear modification factors for each parton flavour are estimated using the well-known Hessian method. The nuclear charm quark distributions are also added into the analysis. We compare the parametrization results with the available data and the results of other nuclear PDFs groups. We found our nuclear PDFs to be in reasonably good agreement with them. The estimates of errors provided by our global analysis are rather smaller than those of other groups. In general, a very good agreement is achieved. We also briefly review the recent heavy-ion collisions data including the first experimental data from the LHC proton + lead and lead + lead run which can be used in the global fits of nuclear PDFs. We highlight different aspects of the high luminosity Pb–Pb and p–Pb data which have been recorded by the CMS Collaboration