Provided are a high performance glass fibre composition, and a glass fibre and a composite material thereof. The content, given in weight percentage, of each component of the glass fibre composition is as follows: 52-67% of SiO2, 12-24% of Al2O3, 0.05-4.5% of Sm2O3 + Gd2O3, less than 2% of Li2O + Na2O + K2O, 10-24% of CaO + MgO + SrO, less than 16% of CaO, less than 13% of MgO, less than 3% of TiO2, and less than 1.5% of Fe2O3. The composition significantly improves the mechanical properties and the thermal stability of glass, significantly reduces the liquidus temperature and the forming temperature of glass, and under equal conditions, significantly reduces the crystallisation rate of glass. The composition is particularly suitable for the tank furnace production of a high performance glass fibre having excellent thermal stability.
Real-time streaming of shape deformations in a shared distributed virtual environment is a challenging task due to the difficulty of transmitting large amounts of 3D animation data to multiple receiving parties at a high frame rate. In this paper, we present a framework for streaming 3D shape deformations, which allows shapes with multi-resolutions to share the same deformations simultaneously in real time. The geometry and motion of deforming mesh or point-sampled surfaces are compactly encoded, transmitted, and reconstructed using the spectra of the manifold harmonics. A receiver-based multi-resolution surface reconstruction approach is introduced, which allows deforming shapes to switch smoothly between continuous multi-resolutions. On the basis of this dynamic reconstruction scheme, a frame rate control algorithm is further proposed to achieve rendering at interactive rates. We also demonstrate an efficient interpolation-based strategy to reduce computing of deformation. The experiments conducted on both mesh and point-sampled surfaces show that our approach achieves efficient performance even if deformations of complex 3D surfaces are streamed. Copyright (c) 2013 John Wiley & Sons, Ltd.
Existing blind image quality assessment (BIQA) methods are mostly opinion-aware. They learn regression models from training images with associated human subjective scores to predict the perceptual quality of test images. Such opinion-aware methods, however, require a large amount of training samples with associated human subjective scores and of a variety of distortion types. The BIQA models learned by opinion-aware methods often have weak generalization capability, hereby limiting their usability in practice. By comparison, opinion-unaware methods do not need human subjective scores for training, and thus have greater potential for good generalization capability. Unfortunately, thus far no opinion-unaware BIQA method has shown consistently better quality prediction accuracy than the opinion-aware methods. Here, we aim to develop an opinion-unaware BIQA method that can compete with, and perhaps outperform, the existing opinion-aware methods. By integrating the features of natural image statistics derived from multiple cues, we learn a multivariate Gaussian model of image patches from a collection of pristine natural images. Using the learned multivariate Gaussian model, a Bhattacharyya-like distance is used to measure the quality of each image patch, and then an overall quality score is obtained by average pooling. The proposed BIQA method does not need any distorted sample images nor subjective quality scores for training, yet extensive experiments demonstrate its superior quality-prediction performance to the state-of-the-art opinion-aware BIQA methods. The MATLAB source code of our algorithm is publicly available at www.comp.polyu.edu.hk/~cslzhang/IQA/ILNIQE/ILNIQE.htm.
Zhang, Lin
Li, Yunchu
Song, Muping
Beausoleil, Raymond G.
Willner, Alan E.
An ultra-small silicon-based microring modulator and filter were proposed to generate and demodulate NRZ DPSK at 10 Gb/s. In this paper, we analyze performance dependencies of the modulator and demodulator under different operating conditions, such as variable laser linewidth, phase shift, demodulator offset and receiver bandwidth. Data quality of the microring-based DPSK transceiver can be optimized with eye-opening improvement of up to 7 dB. Transmission performance of the all-microring-based DPSK signal over a 70-km single mode fiber is compared to that of DPSK using a Mach-Zehnder modulator and a delay-line interferometer. (C) 2008 Optical Society of America.
A method and apparatus of a novel full chip edge-based mask three-dimensional (3D) model for performing photolithography simulation is described. The method applies a thin mask model to a mask design layout to create a thin mask transmission. The method generates a thick mask model that has a plurality of edge-based kernels. The method applies the thick mask model to the mask design layout to create a mask 3D residual. The method combines the thin mask transmission and the mask 3D residual to create a mask 3D transmission.
An FI having an in-situ particle detector and a method for particle detection therein are provided. In one aspect, the FI includes a fan, a substrate support, a particle detector, and an exhaust outlet. The fan, substrate support, and particle detector are arranged such that, in operation, the fan directs air towards the exhaust outlet and over a substrate on the substrate support to create laminar flow. The particle detector, positioned downstream from the substrate support and upstream from the exhaust outlet, analyzes the air and detects particle concentration before the particles are exhausted. The collected particle detection data may be combined with data from other sensors in the FI and used to identify the source of particle contamination. The particle detector may also be incorporated into other system components, including but not limited to, a load-lock or buffer chamber to detect particle concentration therein.