Organic aerosols are ubiquitous in the atmosphere and oxygenated organics a major driver of aerosol growth. The volatility basis set (VBS) as introduced by Donahue et al. (2006, 2011) is often used to simplify partitioning behavior huge variety atmospheric organics. Recently, VBS was dynamically model growth from smallest sizes onwards. This tutorial intended equip reader with necessary tools f...

A strategy for detection of feedstock variations in a continuous pulp digester is presented. A Gaussian Radial Basis Function Neural Network is used to infer these unmeasured variations. The absence of plant data motivates the development of training set data. The efficiency and limitation of the approach is demonstrated with a first principles model.

In the approach to quantum mechanical reactive scattering that we have been pursuing in an earlier paper, the reactive coupling has been described by a non-local exchange interaction in a coupled-channel S&r&linger equation. The results of systematic studies undertaken to identify the most efficient way to include the exchange interaction to infinite order, i.e. exactly, are reported. We find t...

The Ball basis was introduced for cubic polynomials by Ball, and two different generalizations for higher degree m polynomials have been called the Said–Ball and the Wang–Ball basis, respectively. In this paper, we analyze some shape preserving and stability properties of these bases. We prove that the Wang–Ball basis is strictly monotonicity preserving for all m. However, it is not geometrical...

In this paper, an incremental learning model called Resource Allocating Network with Long-Term Memory (RAN-LTM) is extended such that the learning is conducted with some autonomy for the following functions: 1) data collection for initial learning, 2) data normalization, 3) addition of radial basis functions (RBFs), and 4) determination of RBF centers and widths. The proposed learning algorithm...

In this paper a numerical technique is presented for the solution of fuzzy linear Volterra-Fredholm-Hammerstein integral equations. This method is a combination of collocation method and radial basis functions(RBFs).We first solve the actual set are equivalent to the fuzzy set, then answer 1-cut into the equation. Also high convergence rates and good accuracy are obtain with the propose method ...

We demonstrate an implementation of the twoelectron repulsion integrals code for the direct selfconsistent field calculations on a reconfigurable computer. We analyze different strategies and optimization techniques necessary to port the code to SRC-6 reconfigurable computer and provide performance results for models using relatively uncontracted and highly contracted basis sets. Our implementa...

Artificial neural network (ANN) was developed to predict the morphology of TiO2 nanotube prepared by anodization. The collected experimental data was simplified in an innovative approach and used as training and validation data, and the morphology of TiO2 nanotube was considered as three parameters including the degree of order, diameter and length. Applying radial basis function neural network...

In many pieces of music, the composer signals how individual sonic elements (samples, loops, the trumpet section) should be grouped by introducing sources or groups in a layered manner. We propose to discover and leverage the layering structure and use it for both structural segmentation and source separation. We use reconstruction error from non-negative matrix factorization (NMF) to guide str...

In this article experimental work is presented on the identification of the damping parameters in a new defence system, called Minesniper. Simulations have revealed that the standard identification model for the damping parameters with a linear and a quadratic term yields inaccurate results. Therefore, neural networks are used to represent the damping. As the available, noisy training data set ...