Characterization of a wavelength selection method using near-infrared spectroscopy and partial least squares with false nearest neighbors and its application in the detection of the chemical oxygen demand of waste liquid

Abstract

The spectral wavelength selection method is important in near-infrared spectroscopy. Eliminating redundant information and extracting useful information can improve the prediction accuracy and modeling efficiency of the quantitative analysis model for spectral analysis to obtain a near-infrared calibration model with strong predictability and good robustness. This paper proposes a wavelength selection method for near-infrared spectroscopy by combining the partial least squares and false nearest neighbor methods. In this method, the correlation between the characteristic wavelength variables and the measured index is assessed by means of a similarity-based distance measure of the characteristic wavelength variable, and the characteristic wavelength is selected according to the order of the correlation. The method was used to select characteristic wavelengths from the near-infrared spectrum of waste liquid to establish a prediction model for the chemical oxygen demand. Compared with the full-spectrum partial least squares and interval partial least squares based models, the number of characteristic wavelength variables is reduced from 1557 to 176, and the prediction accuracy of the model is improved. This method both simplifies the model and achieves higher prediction accuracy. Therefore, this study provides a novel solution for wavelength selection for multivariate calibration in near-infrared spectroscopy.     

On the use of homogeneous polynomials to develop anisotropic yield functions with applications to sheet forming

This paper investigates the capabilities of several non-quadratic polynomial yield functions to model the plastic anisotropy of orthotropic sheet metal (plane stress). Fourth, sixth and eighth-order homogeneous polynomials are considered. For the computation of the coefficients of the fourth-order polynomial an improved set of analytic formulas is proposed. For sixth and eighth-order polynomials the identification uses optimization. Simple constraints on the optimization process are shown to lead to real-valued convex functions. A general method to extend the above plane stress criteria to full 3D stress states is also suggested. Besides their simplicity in formulation, it is found that polynomial yield functions are capable to model a wide range of anisotropic plastic properties (e.g., the Numisheet’93 mild steel, AA2008-T4, AA2090-T3). The yield functions have then been implemented into a commercial finite element code as constitutive subroutines. The deep drawing of square (Numisheet’93) and cylindrical (AA2090-T3) cups have been simulated. In both cases excellent agreement with experimental data is obtained. In particular, it is shown that non-quadratic polynomial yield functions can simulate cylindrical cups with six or eight ears. We close with a discussion on earing and further examples.     

Non-intrusive hybrid interval method for uncertain nonlinear systems using derivative information

This paper proposes a new non-intrusive hybrid interval method using derivative information for the dynamic response analysis of nonlinear systems with uncertain-butbounded parameters and/or initial conditions. This method provides tighter solution ranges compared to the existing polynomial approximation interval methods. Interval arithmetic using the Chebyshev basis and interval arithmetic using the general form modified affine basis for polynomials are developed to obtain tighter bounds for interval computation.To further reduce the overestimation caused by the "wrapping effect" of interval arithmetic, the derivative information of dynamic responses is used to achieve exact solutions when the dynamic responses are monotonic with respect to all the uncertain variables. Finally, two typical numerical examples with nonlinearity are applied to demonstrate the effectiveness of the proposed hybrid interval method, in particular, its ability to effectively control the overestimation for specific timepoints.     

On the *-Polynomial Identities of a Class of *-Minimal Algebras

Let F be an infinite field. We consider certain block-triangular algebras with involution U _n , with n ∈ ?, having minimal *-exponent. We describe their *-polynomial identities, and in case char.F = 0, their structure as a T _*-ideal under the action of general linear groups. These goals are achieved by means of Y-proper polynomials. We also compute explicitly the irreducible modules occurring in the decomposition of B _Y (U ₃) and their multiplicities.     

An Algebra of Exponential Polynomials as the Cofinite Dual of the Hopf Algebra of Polynomials

We prove that the cofinite dual of the Hopf algebra of polynomials in several variables can be represented as a Hopf algebra ? of exponential polynomials that contains the polynomials as a Hopf subalgebra. We also present some algebras isomorphic to ? whose elements are rational functions or multi-sequences.     

Pointwise estimates for relative fundamental solutions of heat equations in $${\mathbb{R} \times \mathbb{C}}$$

Let be a subharmonic, nonharmonic polynomial and a parameter. Define , a closed, densely defined operator on . If and , we solve the heat equations , u(0,z) = f(z) and , . We write the solutions via heat semigroups and show that the solutions can be written as integrals against distributional kernels. We prove that the kernels are C ^∞ off of the diagonal {(s, z, w) : s = 0 and z = w} and find pointwise bounds for the kernels and their derivatives.      

A polynomial algorithm for one problem of guillotine cutting

We consider the problem of guillotine cutting a rectangular sheet into two rectangular pieces without rotations. The question is whether there exists a cutting pattern with given numbers of occurrences of both rectangular pieces. A polynomial time algorithm is described to construct the convex hull of solutions to this problem.     

Choiceless polynomial time

Turing machines define polynomial time (PTime) on strings but cannot deal with structures like graphs directly, and there is no known, easily computable string encoding of isomorphism classes of structures. Is there a computation model whose machines do not distinguish between isomorphic structures and compute exactly PTime properties? This question can be recast as follows: Does there exist a logic that captures polynomial time (without presuming the presence of a linear order)? Earlier, one of us conjectured a negative answer. The problem motivated a quest for stronger and stronger PTime logics. All these logics avoid arbitrary choice. Here we attempt to capture the choiceless fragment of PTime. Our computation model is a version of abstract state machines (formerly called evolving algebras). The idea is to replace arbitrary choice with parallel execution. The resulting logic expresses all properties expressible in any other PTime logic in the literature. A more difficult theorem shows that the logic does not capture all of PTime.