(E)-2-[2-(Penta­fluoro­phen­yl)ethen­yl]-8-quinolyl acetate

The title compound, C19H10F5NO2, was synthesized by the 1:1 condensation of 2-methyl-8-hydroxy­quinaldine with penta­fluoro­benzaldehyde. It crystallizes with two almost identical mol­ecules in the asymmetric unit. The penta­fluoro­benzene ring is essentially coplanar with the quinoline ring, forming dihedral angles of 2.49 (17) and 8.72 (16)° in the two mol­ecules

Effects of psycholinguistic variables on writing performance of normal elderly with different education levels

A dissertation submitted in partial fulfilment of the requirements for the Bachelor of Science (Speech and Hearing Sciences), The University of Hong Kong, June 30, 2005.Thesis (B.Sc)--University of Hong Kong, 2006published_or_final_versionSpeech and Hearing SciencesBachelorBachelor of Science in Speech and Hearing Science

Efficient, massively parallel eigenvalue computation

In numerical simulations of disordered electronic systems, one of the most common approaches is to diagonalize random Hamiltonian matrices and to study the eigenvalues and eigenfunctions of a single electron in the presence of a random potential. An effort to implement a matrix diagonalization routine for real symmetric dense matrices on massively parallel SIMD computers, the Maspar MP-1 and MP-2 systems, is described. Results of numerical tests and timings are also presented

Automatic Side-Scan Sonar Image Enhancement in Curvelet Transform Domain

We propose a novel automatic side-scan sonar image enhancement algorithm based on curvelet transform. The proposed algorithm uses the curvelet transform to construct a multichannel enhancement structure based on human visual system (HVS) and adopts a new adaptive nonlinear mapping scheme to modify the curvelet transform coefficients in each channel independently and automatically. Firstly, the noisy and low-contrast sonar image is decomposed into a low frequency channel and a series of high frequency channels by using curvelet transform. Secondly, a new nonlinear mapping scheme, which coincides with the logarithmic nonlinear enhancement characteristic of the HVS perception, is designed without any parameter tuning to adjust the curvelet transform coefficients in each channel. Finally, the enhanced image can be reconstructed with the modified coefficients via inverse curvelet transform. The enhancement is achieved by amplifying subtle features, improving contrast, and eliminating noise simultaneously. Experiment results show that the proposed algorithm produces better enhanced results than state-of-the-art algorithms