Journal of Applied & Computational Mathematics

Debt collection is a massive industry, with in USA alone more than $50 billion recovered each year. However, the information available is often limited and incomplete, and predicting whether a given debtor would repay is inherently a challenging task. This has amplified research on debt recovery classification and prediction models of late. This report considers three main mathematical, data mining and statistical models in debt recovery classification, in logistic regression, artificial neural networks and affinity analysis. It also compares the effectiveness of the above mentioned tools in evaluating whether a debt is likely to be repaid. The construction and analysis of the models were based on a fairly large unbalanced data sample provided by a debt collection agency. It has been shown that all three models could classify the debt repayments with a considerable accuracy, if the assumptions of the models are satisfied

In this paper the solute transport in a fractured-porous medium is considered with equilibrium adsorption. One the basis of numerical results an influence of adsorption on solute transport characteristics is estimated.

If the Simple fractions of 1 such as 0→¼→½→¾→ till the marking of 1 give a one value, the Mixed fractions of 1 such as 1→1¼→1½→1¾→till the fullness of 1 further give the Other 1 value, where then totally there are two 1^s. From the added value of the two values of these two 1^s, here Digit 2 originates. Similar to the Digit Other 1, Digit 2 is having only the Mixed fractions such as 2→2¼→2½→2¾→ till the fullness of 2 and similarly Digit 3 is having only the Mixed fractions such as 3→3¼→3½→3¾→till the fullness of 3, and so on with the same stage of the Mixed fractions till Digit 9. This is because there are no Simple fractions for 2 or 3 or for any further digits till Digit 9.

Powder diffraction analysis and the data profile fitting represent the phase identification of a crystalline material which gives information about its unit cell dimensions. In a polycrystalline sample it is inevitable that certain information is lost as a result of the random orientation of the crystallites. So whole Pattern fitting Structure Refinement is now widely accepted to be an exceptionally valuable method for structural analysis of nearly all classes of crystalline materials not available as single crystals. Least squares approach which means manually refining a model to match experimental data can be said as Rietveld analysis which is an extended refinement analysis of a given diffraction data.

In this paper, we investigate the stabilization by means of homogeneous feedback of degree zero of a class of bilinear systems in ℝ³.