The algebraic immunity of cryptographic Boolean functions is studied in this paper. Proper modifications of functions achieving maximum algebraic immunity are proved, in order to yield new functions of also maximum algebraic immunity. It is shown that the derived results apply to known classes of functions. Moreover, two new efficient algorithms to produce functions of guaranteed maximum algebr...

Irrigation, salinity and nitrogen (N) are the three major limiting environmental factors inmaize yield potentials especially in arid and semi-arid regions. An integrated water and N MaizeSimulation Model (MSM) was modified for salinity conditions using 2009-2010 fieldexperiments data in southwest of Iran. Irrigation levels were: I1=1.0ETc+0.25ETc as normalleaching amount, I2=0.75I1 and I3=0.5I1...

The objective of this paper is to present a technique for order preference by similarity to ideal solution (TOPSIS) algorithm to linear fractional bi-level multi-objective decision-making problem. TOPSIS is used to yield most appropriate alternative from a finite set of alternatives based upon simultaneous shortest distance from positive ideal solution (PIS) and furthest distance from negative ...

this paper is concerned with the study of the existence of positive solutions for a navier boundaryvalue problem involving the p-biharmonic operator; the right hand side of problem is a nonsmoothfunctional with variable parameters. the existence of at least three positive solutions is establishedby using nonsmooth version of a three critical points theorem for discontinuous functions. our resul...

The scope of refinable functions in wavelet theory is focused to localized functions. In our paper we like to widen that scope, in particular we show that all polynomial functions are refinable. This may yield an interesting notion of convolution of polynomials.

Formulas for variances of plane parameters fitted with Nonlinear Least Squares to point clouds acquired by 3D imaging systems (e.g., LADAR) are derived. Two different error objective functions used in minimization are discussed: the orthogonal and the directional functions. Comparisons of corresponding formulas suggest the two functions can yield different results when applied to the same dataset.