The dielectric constant of metastable ε-Ga2O3 was evaluated for the first time by using a transparent heteroepitaxial structure of ε-Ga2O3/indium tin oxide/yttria-stabilized zirconia.
Despite the supposed simplicity of double-closed shell nuclei, conventional coupled-channels calculations, that include all of the known collective states of the target and projectile, give a poor fit to the fusion cross section for the 16O + 208Pb system. The discrepancies are highlighted through the experimental barrier distribution and logarithmic derivative, that are both well defined by the precise experimental fusion data available. In order to broaden our search for possible causes for this anomaly, we revisit this system and include in our calculations a large number of noncollective states of the target, whose spin, parity, excitation energy, and deformation parameter are known from high-precision proton inelastic-scattering measurements. Although the new coupled-channels calculations modify the barrier distribution, the disagreement with experiment remains both for fusion and for quasi-elastic (QE) scattering. We find that the Q-value distributions for large-angle QE scattering become rapidly more important as the incident energy increases, reflecting the trend of the experimental data. The mass-number dependence of the noncollective excitations is discussed
Palm region extraction is one of the most important processes in palmprint recognition, since the accuracy of extracted palm regions has a significant impact on recognition performance. Especially in contactless recognition systems, a palm region has to be extracted from a palm image by taking into consideration a variety of hand poses. Most conventional methods of palm region extraction assume that all the fingers are spread and a palm faces to a camera. This assumption forces users to locate his/her hand with limited pose and position, resulting in impairing the flexibility of the contactless palmprint recognition system. Addressing the above problem, this paper proposes a novel palm region extraction method robust against hand pose. Through a set of experiments using our databases which contains palm images with different hand pose and the public database, we demonstrate that the proposed method exhibits efficient perfomance compared with conventional methods.
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