Preparation of magnetic polyurethane rigid foam nanocomposites

Super paramagnetic Fe₃O₄@SiO₂ nanoparticle was incorporated into polyurethane rigid foams in order to prepare new corresponded magnetic nanocomposite foams via one-shot method. The core–shell-structured nanoparticles were prepared by sol–gel method and characterized by transmission electron microscopy, X-ray diffraction, as well as Fourier transform infrared spectroscopy techniques. Magnetic nanoparticles were used up to 3 % in the foam formulations and the samples prepared successfully. Thermal, mechanical, and magnetic properties of nanocomposites were studied and the results showed superior properties in comparison with pristine foams.     

An efficient nonmonotone trust-region method for unconstrained optimization

The monotone trust-region methods are well-known techniques for solving unconstrained optimization problems. While it is known that the nonmonotone strategies not only can improve the likelihood of finding the global optimum but also can improve the numerical performance of approaches, the traditional nonmonotone strategy contains some disadvantages. In order to overcome to these drawbacks, we introduce a variant nonmonotone strategy and incorporate it into trust-region framework to construct more reliable approach. The new nonmonotone strategy is a convex combination of the maximum of function value of some prior successful iterates and the current function value. It is proved that the proposed algorithm possesses global convergence to first-order and second-order stationary points under some classical assumptions. Preliminary numerical experiments indicate that the new approach is considerably promising for solving unconstrained optimization problems.     

A web-based workforce management system for Sainsburys Supermarkets Ltd

Labour scheduling plays an important and critical role in Sainsburys day to day operations and profitability. The integrated workforce management solution for Sainsburys is an intelligent solution for the operational deployment of human resources, integrated business forecasting, generation and calculation of workload and staff scheduling. The workforce management technology has provided Sainsburys with a fully web-based and centralised system that produces optimised schedules for all employees satisfying the forecasted demand of work with granularity of fifteen minutes. The system is configured to respect all operational and business requirements as well as employee contractual constraints. This paper introduces the workforce management solution system designed, developed and implemented for Sainsburys. We concentrate on two modelling structures, namely the work pattern model and optimisation model, and briefly discuss the optimisation process.     

An efficient Levenberg–Marquardt method with a new LM parameter for systems of nonlinear equations

A modified Levenberg–Marquardt method for solving singular systems of nonlinear equations was proposed by Fan [J Comput Appl Math. 2003;21;625–636]. Using trust region techniques, the global and quadratic convergence of the method were proved. In this paper, to improve this method, we decide to introduce a new Levenberg–Marquardt parameter while also incorporate a new nonmonotone technique to this method. The global and quadratic convergence of the new method is proved under the local error bound condition. Numerical results show the new algorithm is efficient and promising.     

Artificial neural network for quantitative determination of total protein in yogurt by infrared spectrometry

A method has been introduced for quantitative determination of protein content in yogurt samples based on the characteristic absorbance of protein in 1800-1500 cm^− 1 spectral region by mid-FTIR spectroscopy and chemometrics. Successive Projection Algorithm (SPA) wavelength selection procedure, coupled with feed forward Back-Propagation Artificial Neural Network (BP-ANN) model was the benefited chemometric technique. Relative Error of Prediction (REP) in BP-ANN and SPA-BP-ANN methods for training set was 7.25 and 3.70 respectively. Considering the complexity of the sample, the ANN model was found to be reliable, while the proposed method is rapid and simple, without any sample preparation step.     

Numeric kinetic energy operators for molecules in polyspherical coordinates

Generalized curvilinear coordinates, as, e.g., polyspherical coordinates, are in general better adapted to the resolution of the nuclear Schro?dinger equation than rectilinear ones like the normal mode coordinates. However, analytical expressions of the kinetic energy operators (KEOs) for molecular systems in polyspherical coordinates may be prohibitively complicated for large systems. In this paper we propose a method to generate a KEO numerically and bring it to a form practicable for dynamical calculations. To examine the new method we calculated vibrational spectra and eigenenergies for nitrous acid (HONO) and compare it with results obtained with an exact analytical KEO derived previously [F. Richter, P. Rosmus, F. Gatti, and H.-D. Meyer, J. Chem. Phys. 120, 6072 (2004)]. In a second example we calculated π → π* photoabsorption spectrum and eigenenergies of ethene (C(2)H(4)) and compared it with previous work [M. R. Brill, F. Gatti, D. Lauvergnat, and H.-D. Meyer, Chem. Phys. 338, 186 (2007)]. In this ethene study the dimensionality was reduced from 12 to 6 by freezing six internal coordinates. Results for both molecules show that the proposed method for obtaining an approximate KEO is reliable for dynamical calculations. The error in eigenenergies was found to be below 1 cm(-1) for most states calculated.     

Post Recognition Speech Localization

How much does knowledge regarding a certain spoken word or phrase help with its localization? This is a very fundamental question for speech processing, and will be partially addressed in this paper. In particular, this work will utilize prior information regarding the contents of a speech signal in order to improve the artificial localization of it using Time delay of arrival (TDOA) between two microphones. The prior information, which is used to develop a very simple frequency-selective phase transform (FPT), increases the effective SNR by only using a subset of the highest SNR frequencies in the Phase Transform. Simulations in a reverberant environment show that the proposed approach can more robustly and accurately localize speech sources. For 20 ms signal segments, it is shown that using a subset of 45 percent of available speech frequency bins is superior to using 30, 60, or 100, where using 100 corresponds to the standard Phase Transform.     

A novel technique based on diffuse reflectance near-infrared spectrometry and back-propagation artificial neural network for estimation of particle size in TiO2 nano particle samples

Determination of particle size is one of the critical parameters in nanotechnology. The relationship between particle size and diffuse reflectance (DR) spectra in near-infrared region has been applied to introduce a method for estimation of particle size. Back-propagation artificial neural network (BP-ANN) as a nonlinear model was applied to estimate average particle size based on near-infrared diffuse reflectance spectra. Thirty five different nano TiO₂ samples with different particle size were analyzed by DR-FTNIR spectrometry and the obtained data were processed by BP-ANN. The network was trained by 30 samples and was evaluated by the remaining 5 samples. In order to establish whether the new method is applicable for estimation of particle size of nano structured samples, the optimized model was applied to analyze 44 nano TiO₂ samples. It was observed that ANN using the back-propagation algorithm is capable of generalization and could correctly predict the average particle size of nano-sized particles.     

An improved adaptive trust-region algorithm

This paper gives a variant trust-region method, where its radius is automatically adjusted by using the model information gathered at the current and preceding iterations. The primary aim is to decrease the number of function evaluations and solving subproblems, which increases the efficiency of the trust-region method. The next aim is to update the new radius for large-scale problems without imposing too much computational cost to the scheme. Global convergence to first-order stationary points is proved under classical assumptions. Preliminary numerical experiments on a set of test problems from the CUTEst collection show that the presented method is promising for solving unconstrained optimization problems.