Unequal Error Protected JPEG 2000 Broadcast Scheme with Progressive Fountain Codes

This paper proposes a novel scheme, based on progressive fountain codes, for broadcasting JPEG 2000 multimedia. In such a broadcast scheme, progressive resolution levels of images/video have been unequally protected when transmitted using the proposed progressive fountain codes. With progressive fountain codes applied in the broadcast scheme, the resolutions of images (JPEG 2000) or videos (MJPEG 2000) received by different users can be automatically adaptive to their channel qualities, i.e. the users with good channel qualities are possible to receive the high resolution images/vedio while the users with bad channel qualities may receive low resolution images/vedio. Finally, the performance of the proposed scheme is evaluated with the MJPEG 2000 broadcast prototype

Rateless Codes with Progressive Recovery for Layered Multimedia Delivery

This paper proposes a novel approach, based on unequal error protection, to enhance rateless codes with progressive recovery for layered multimedia delivery. With a parallel encoding structure, the proposed Progressive Rateless codes (PRC) assign unequal redundancy to each layer in accordance with their importance. Each output symbol contains information from all layers, and thus the stream layers can be recovered progressively at the expected received ratios of output symbols. Furthermore, the dependency between layers is naturally considered. The performance of the PRC is evaluated and compared with some related UEP approaches. Results show that our PRC approach provides better recovery performance with lower overhead both theoretically and numerically

Deposition, microstructure and magnetic anisotropy of cobalt ferrite thin films

Ph.DDOCTOR OF PHILOSOPH

Gate defined quantum dot realized in a single crystalline InSb nanosheet

Single crystalline InSb nanosheet is an emerging planar semiconductor material with potential applications in electronics, infrared optoelectronics, spintronics and topological quantum computing. Here we report on realization of a quantum dot device from a single crystalline InSb nanosheet grown by molecular-beam epitaxy. The device is fabricated from the nanosheet on a Si/SiO2 substrate and the quantum dot confinement is achieved by top gate technique. Transport measurements show a series of Coulomb diamonds, demonstrating that the quantum dot is well defined and highly tunable. Tunable, gate-defined, planar InSb quantum dots offer a renewed platform for developing semiconductor-based quantum computation technology.Comment: 12 pages, 4 figure

Testing for homogeneity of gametic disequilibrium across strata

Copyright © 2007 Yin et al. Background: Assessing the non-random associations of alleles at different loci, or gametic disequilibrium, can provide clues about aspects of population histories and mating behavior and can be useful in locating disease genes. For gametic data which are available from several strata with different allele probabilities, it is necessary to verify that the strata are homogeneous in terms of gametic disequilibrium. Results: Using the likelihood score theory generalized to nuisance parameters we derive a score test for homogeneity of gametic disequilibrium across several independent populations. Simulation results demonstrate that the empirical type I error rates of our score homogeneity test perform satisfactorily in the sense that they are close to the pre-chosen 0.05 nominal level. The associated power and sample size formulae are derived. We illustrate our test with a data set from a study of the cystic fibrosis transmembrane conductance regulator gene. Conclusion: We propose a large-sample homogeneity test on gametic disequilibrium across several independent populations based on the likelihood score theory generalized to nuisance parameters. Our simulation results show that our test is more reliable than the traditional test based on the Fisher's test of homogeneity among correlation coefficients. © 2007 Yin et al; licensee BioMed Central Ltd.This research was supported by the National Natural Science Foundation of China (Grant Numbers 10431010 and 10701022), National 973 Key Project of China (2007CB311002), NCET-04-0310, EYTP, the Jilin Distinguished Young Scholars Program (Grant Number 20030113) and the Program Innovative Research Team (PCSIRT) in University (#IRT0519). The work of ML Tang was fully supported by a grant from the Research Grant Council of the Hong Kong Special Administration (Project no. HKBU261007)

Anisotropic Pauli spin-blockade effect and spin-orbit interaction field in an InAs nanowire double quantum dot

We report on experimental detection of the spin-orbit interaction field in an InAs nanowire double quantum dot device. In the spin blockade regime, leakage current through the double quantum dot is measured and is used to extract the effects of spin-orbit interaction and hyperfine interaction on spin state mixing. At finite magnetic fields, the leakage current arising from the hyperfine interaction is suppressed and the spin-orbit interaction dominates spin state mixing. We observe dependence of the leakage current on the applied magnetic field direction and determine the direction of the spin-orbit interaction field. We show that the spin-orbit field lies in a direction perpendicular to the nanowire axis but with a pronounced off-substrate-plane angle. It is for the first time that such an off-substrate-plane spin-orbit field in an InAs nanowire has been detected. The results are expected to have an important implication in employing InAs nanowires to construct spin-orbit qubits and topological quantum devices.Comment: 20 pages, 5 figures, Supporting Informatio

Uncertainty Quantification by Convolutional Neural Network Gaussian Process Regression with Image and Numerical Data

Uncertainty Quantification (UQ) plays a critical role in engineering analysis and design. Regression is commonly employed to construct surrogate models to replace expensive simulation models for UQ. Classical regression methods suffer from the curse of dimensionality, especially when image data and numerical data coexist, which makes UQ computationally unaffordable. In this work, we propose a Convolutional Neural Network (CNN) based framework, which accommodates both image and numerical data. We first transform numerical data into images and then combine them with existing image data. The combined images are fed to CNN for regression. To obtain the model uncertainty, we integrate CNN with Gaussian Process (GP), which results in the mixed network CNN-GP. The simulation results show that CNN-GP can build accurate surrogate models for UQ with mixed data and that CNN-GP can also provide the uncertainty associated with the model prediction