A comparison of transformation methods for evaluating two‐dimensional weakly singular integrals

Accurate numerical evaluation of integrals arising in the boundary element method is fundamental to achieving useful results via this solution technique. In this paper, a number of techniques are considered to evaluate the weakly singular integrals which arise in the solution of Laplace's equation in three dimensions and Poisson's equation in two dimensions. Both are two‐dimensional weakly singular integrals and are evaluated using (in a product fashion) methods which have recently been used for evaluating one‐dimensional weakly singular integrals arising in the boundary element method. The methods used are based on various polynomial transformations of conventional Gaussian quadrature points where the transformation polynomial has zero Jacobian at the singular point. Methods which split the region of integration into sub‐regions are considered as well as non‐splitting methods. In particular, the newly introduced and highly accurate generalized composite subtraction of singularity and non‐linear transformation approach (GSSNT) is applied to various two‐dimensional weakly singular integrals. A study of the different methods reveals complex relationships between transformation orders, position of the singular point, integration kernel and basis function. It is concluded that the GSSNT method gives the best overall results for the two‐dimensional weakly singular integrals studied. Copyright © 2002 John Wiley & Sons, Ltd.     

Desalination by distillation and by reverse osmosis — trends towards the future

As the requirement for fresh water increases worldwide, there is a need for more and more plants that are able to treat non-conventional water sources. Sea water has become an important source of fresh water in many arid regions. This feature provides an overview of recent process improvements in sea water desalination using reverse osmosis, multi-stage flash, multi-effect distillation and electrodialysis. Areas discussed include the use of alternative energy sources (wind energy, solar energy and nuclear energy) for reverse osmosis or distillation processes, and the impact of the different desalination process on the environment. Also covered are the implementation of hybrid processes in sea water desalination, and the pretreatment of desalination plants by pressure-driven membrane processes.     

Light-induced electron spin polarization in the ground state of water-soluble copper porphyrins

Light-induced spin-polarized transient EPR spectra are reported for several water-soluble copper porphyrins. The spectra are assigned to the doublet ground state, with emissive spin polarization resulting from photoexcitation and subsequent electronic relaxation. In contrast to other systems for which polarization of a doublet ground state has been observed, the exchange interactions in the copper porphyrins are strong and the geometry is fixed. It is proposed that intersystem crossing from the photoexcited trip-doublet to the trip-quartet state can lead to net polarization of the spin system and that this polarization is maintained during electronic decay, possibly via charge-transfer and exciplex states. The intensity of the observed spin polarization is essentially independent of the molecular orientation in the external field, but is strongly dependent on the nature of the charged peripheral groups. Possible reasons for this behavior are discussed.     

Hopping and optical absorption of electrons in nano-porous crystal 12CaO·7Al2O3

Recently it has been discovered that a nano-porous main group oxide 12CaO·7Al₂O₃ (C12A7) can be converted from a wide-gap insulator to a good transparent conductor. Using ab initio modelling we explain good conductivity of this material by very small barriers for hopping of localised electrons between neighbouring positive cages. We show that optical absorption of C12A7 in infrared region and at energies higher than 2.7 eV is due to inter-cage and intra-cage electron transitions, respectively. The proposed mechanisms can be useful in further search for conducting transparent media.     

Novel level-identifying circuit for flash multilevel memories

This paper presents a high-speed, small-area circuit specifically designed to identify the levels in the read out operation of a flash multilevel memory. The circuit is based on the analog computation of the Euclidean distance between the current read out from a memory cell and the reference currents that represent the different logic levels. An experimental version of the circuit has been integrated in a standard double-metal 0.7-μm CMOS process with a die area of only 140×100 μm². Operating under a 5-V power supply, this circuit identifies the read-out current of a memory cell, and associates it with the appropriate logic level in 9 ns     

Drift hole mobility in strained and unstrained doped Si1-xGex alloys

Results of the drift hole mobility in strained and unstrained SiGe alloys are reported for Ge fractions varying from 0 to 30% and doping levels of 10¹⁵-10¹⁹ cm^-3. The mobilities are calculated taking into account acoustic, optical, alloy, and ionized-impurity scattering. The mobilities are then compared with experimental results for a boron doping concentration of 2×10¹⁹ cm^-3. Good agreement between experimental and theoretical values is obtained. The results show an increase in the mobility relative to that of silicon     

Artificial neural networks for coordination and control: The portability of experiential representations

It is time to locate connectionist representation theory in the new wave of robotics research. The utility of representations developed in artificial neural networks (ANNs) during learning has been demonstrated in cognitive science research since the 1980s. The research reported here puts learned representations to work in a decentered control task, the disembodied arm problem, in which a mobile robot operates an arm fixed to a table to pick up objects. There is no physical linkage between the arm and the robot and so the robot's point of view must be decentered. This is done by developing a modular Artificial Neural Net system in three stages: (i) a classifier net is trained with laser scan data to output transformationally invariant position classes; (ii) an arm net is trained for picking up objects; (iii) an inter net is trained to communicate and coordinate the sensing and acting. The completed system is shown to create new nonsymbolic transformationally invariant representations in order to perform the effective generalization of decentered viewpoints.