Kinetic Characteristics of Amino Acid Salt Crystallization in Methanol‐Water System

Nucleation and growth mechanisms and kinetics of crystals of an amino acid salt were investigated in a methanol‐water system by measuring and evaluating the induction time as a function of the supersaturation ratio and temperature in batch salting out crystallization experiments. Discrimination between the possible crystallization mechanisms, and estimation of the kinetic parameters were carried out using nonlinear parameter identification. The results concerning the growth mechanism obtained were checked additionally by measuring the induction time as a function of number density of seed crystals.     

Efficient design and operation of a data acquisition system for pressurized pipeline systems.

The unsteady flow analysis of pipeline systems provides useful guidelines for implementing data acquisition components such as data filtering ranges, sensor locations and sampling frequencies. A theoretical integration among hydraulics, free vibration analysis and signal processing is proposed for a comprehensive approach aiming at enhanced design and operation of data acquisition system. Transient analysis is performed to extract flow variation by a valve modulation in a pipeline system. Frequency transformation analysis is developed to convert pressure variations between time domain and frequency domain. Free vibration analysis provides spatial distribution of impedance characteristics and pressure variation for determining optimum sensor location. A real-time filter can be designed to secure valid signals of any particular unsteady event. Hypothetical and experimental applications show that the proposed method has potentials of the leakage detection of a pipeline system as well as an efficient design of data acquisition system.     

Special Effect Pigments Based on Silica Flakes

A new class of special effect pigments based on synthetically manufactured silica flakes coated with metal oxides was developed and introduced into the market. Silica flake pigments show extraordinary color effects such as improved interference and strong angle-dependent behavior. They can be used in automotive paints, industrial paints, plastics, and printing inks.     

Recovery of gold cyanide using inherently conducting polymers

Removal of gold from basic solutions containing [Au(CN)₂]^? has been demonstrated using the inherently conducting polymer polypyrrole. Polymers containing sulfonated aromatic dopants have been found to display a significant ability to remove gold from such solutions. Experiments performed in solutions containing both gold and copper cyanide complexes indicate that the recovery process is not highly selective. However, the polypyrroles used display significantly faster rates of gold recovery than activated carbon. © 2003 Society of Chemical Industry     

Valorisation of waste fractions from autohydrolysis of selected lignocellulosic materials

Non‐isothermal processing of lignocellulosic materials in aqueous media (autohydrolysis reaction) under mild conditions leads to solutions containing valuable chemicals (oligosaccharides, sugars and acetic acid) and other, undesired, compounds (belonging to the extractive and acid‐soluble lignin fractions) which have to be removed in further purification treatments. Liquors obtained by non‐isothermal autohydrolysis of Eucalyptus globulus wood and corncobs under a variety of operational conditions were extracted with ethyl acetate in order to remove non‐saccharide components, and the suitability of the fraction dissolved in the organic phase was assayed for possible utilisation as an antioxidant. The yield and antioxidant activity of ethyl acetate extracts (measured by the α,α‐diphenyl‐β‐picrylhydrazyl (DPPH) radical scavenging capacity) showed a strong dependence on the autohydrolysis conditions. The antioxidant activity of extracts obtained under selected operational conditions compared well with synthetic antioxidants. © 2003 Society of Chemical Industry     

Using the magneto-optical Kerr effect to study magnetization processes in two-dimensional magnonic crystals based on YIG thin films

The magneto-optical Kerr effect for red (628 nm) and green (532 nm) light is used to study magnetization processes in 2D magnonic crystals obtained by etching pits with the diameter D ≈ 32 μm to a depth of t ≤ 2 μm in a 16.1-μm-thick film of yttrium iron garnet (YIG). Hysteresis loops obtained in the case of the inplane crystal magnetization at 628 nm are characterized by lower saturation fields H _s and higher remanent magnetizations than those obtained at 532 nm, a result that is attributed to different absorption coefficients of the YIG film at these wavelengths. This difference between the magnetization curves reflects the fact that the magnonic-crystal surface probed with the green light makes a greater contribution to the magneto-optical Kerr effect. Therefore, the green light is more sensitive to the demagnetizing fields, which govern magnetization processes in the magnonic crystals.     

Training and optimization of an artificial neural network controlling a hybrid power filter

A hybrid power compensator (HPC) consisting of a static VAr compensator and a dynamic compensator needs to be optimally controlled during the compensation of nonlinear loads. The HPC must be controlled to meet minimum requirements in terms of power factor and harmonic distortion, while at the same time minimizing its total cost. An artificial neural network (ANN) is used to control the HPC amidst a very dynamic power system environment. The performance of a reference ANN is evaluated while controlling an HPC connected to a typical nonlinear industrial load. The training and performance of the ANN is then optimized in terms of training set size, training set packing and ANN topology and the performance compared to the reference ANN. This paper highlights the importance of optimising the mentioned ANN parameters to achieve optimum ANN training and modeling accuracy. The results obtained reveals that the application of an ANN in controlling an HPC is feasible given that the ANN parameters are chosen appropriately.     

A VQ-based blind image restoration algorithm

Learning-based algorithms for image restoration and blind image restoration are proposed. Such algorithms deviate from the traditional approaches in this area, by utilizing priors that are learned from similar images. Original images and their degraded versions by the known degradation operator (restoration problem) are utilized for designing the VQ codebooks. The codevectors are designed using the blurred images. For each such vector, the high frequency information obtained from the original images is also available. During restoration, the high frequency information of a given degraded image is estimated from its low frequency information based on the codebooks. For the blind restoration problem, a number of codebooks are designed corresponding to various versions of the blurring function. Given a noisy and blurred image, one of the codebooks is chosen based on a similarity measure, therefore providing the identification of the blur. To make the restoration process computationally efficient, the principal component analysis (PCA) and VQ-nearest neighbor approaches are utilized. Simulation results are presented to demonstrate the effectiveness of the proposed algorithms.