Parallel multilevel solvers for the cardiac electro-mechanical coupling

We develop a parallel solver for the cardiac electro-mechanical coupling. The electric model consists of two non-linear parabolic partial differential equations (PDEs), the so-called Bidomain model, which describes the spread of the electric impulse in the heart muscle. The two PDEs are coupled with a non-linear elastic model, where the myocardium is considered as a nearly-incompressible transversely isotropic hyperelastic material. The discretization of the whole electro-mechanical model is performed by Q1 finite elements in space and a semi-implicit finite difference scheme in time. This approximation strategy yields at each time step the solution of a large scale ill-conditioned linear system deriving from the discretization of the Bidomain model and a non-linear system deriving from the discretization of the finite elasticity model. The parallel solver developed consists of solving the linear system with the Conjugate Gradient method, preconditioned by a Multilevel Schwarz preconditioner, and the non-linear system with a Newton–Krylov-Algebraic Multigrid solver. Three-dimensional parallel numerical tests on a Linux cluster show that the parallel solver proposed is scalable and robust with respect to the domain deformations induced by the cardiac contraction.     

Multilevel memory characteristics by light-assisted programming in floating-gate organic thin-film transistor nonvolatile memory

In this work, we study charge trapping in floating-gate organic thin-film transistor nonvolatile memories (FG-OTFT-NVMs) fabricated by a simple method. The inner discrete distribution aluminum nanoparticles (Al-Nps) and the continuous compact thin alumina film were formed to act as the floating-gate and the tunneling dielectric layer, respectively by thermally evaporated Al at a slow rate and then heat annealed in dry air. The devices exhibited remarkable photoresponse and memory effect. Compared with the unidirectional threshold voltage (V_T) shifts of memories by programming/erasing (P/E) in dark, larger bidirectional V_T shifts were obtained by light-assisted programming, and therefore the memory performances were enhanced. A multilevel memory behavior was observed in our memories, which depended on programming conditions. The charge trapping mechanisms of memories operated in dark and under illumination are discussed, respectively. The results indicate that optimal memory performance requires charge carriers of both polarities, because it is a very efficient method to enlarge the memory window and to lower the P/E voltage by overwriting trapped charges by injected charges of opposite polarity.     

误码信道中分布式视频编码优化重建算法

针对分布式视频编码在误码环境下部分比特面解码失败,单一区间重建导致视频质量下降的情况,提出了一种多量化区间优化重建算法。该算法充分利用所有连续或不连续的正确解码比特面进行重组,从而得到多个候选的量化区间,并根据边信息与这些区间的位置关系找出最佳的解码区间。相较于传统的单一区间的重建算法,在误码环境中该算法可以更准确地重建出正确解码值。实验结果表明,所提出的算法性能明显优于单一区间的重建算法,在错误比特面错误率相同时,所提算法解码视频的峰值信噪比最大分别有1.2 dB和3.0 dB左右的提升。     

Global optimization of multilevel electricity market models including network design and graph partitioning

We consider the combination of a network design and graph partitioning model in a multilevel framework for determining the optimal network expansion and the optimal zonal configuration of zonal pricing electricity markets, which is an extension of the model discussed in Grimm et al. (2019) that does not include a network design problem. The two classical discrete optimization problems of network design and graph partitioning together with nonlinearities due to economic modeling yield extremely challenging mixed-integer nonlinear multilevel models for which we develop two problem-tailored solution techniques. The first approach relies on an equivalent bilevel formulation and a standard KKT transformation thereof including novel primal-dual bound tightening techniques, whereas the second is a tailored generalized Benders decomposition. For the latter, we strengthen the Benders cuts of Grimm et al. (2019) by using the structure of the newly introduced network design subproblem. We prove for both methods that they yield global optimal solutions. Afterward, we compare the approaches in a numerical study and show that the tailored Benders approach clearly outperforms the standard KKT transformation. Finally, we present a case study that illustrates the economic effects that are captured in our model.     

联合信道网络编码研究综述

网络编码技术可以提高网络吞吐量和传输性能,均衡网络负载。在无线传感器网络中,应用网络编码和信道编码联合编码技术可以降低节点数据处理复杂度,大幅提升系统整体性能。基于传统网络编码模型,在节点中加入数据调制功能,可以实现网络编码和信道编码的联合编码,信道编码则采用各方面性能较好的Turbo码和LDPC码。结果表明,在10-4误码率下,联合编码方案的信噪比相比于传统编码方案有1.5 dB的节省。     

基于TMS320DM8168的视频编码系统研究与实现

随着信息技术的进步,空间对地成像已朝着高清、多路方向发展。基于通用DSP和H.264/AVC视频编码标准的实时视频压缩系统,由于具有开发周期短、可靠性高、处理速度快、便于升级以及体积小、功耗低、适应性强等优点,可以为新的需求提供解决方案,研究基于通用DSP、采用先进视频压缩技术的实时视频编码器具有重要意义。为满足越来越多的高清视频采集、编码和传输的应用需求,基于TI的新一代多核DSP TMS320DM8168芯片,给出了方案的设计与实现,在该系统上实现了H.264视频编码算法,可对输入的双路1080p视频进行60 fps实时编码压缩。方案的主处理器只需一片DSP,与传统多路视频压缩方案需要多片处理器相比,这种高度集成方案降低了部件数量和物料(BOM)成本、功耗需求,缩小了PCB尺寸,提高系统集成度。     

Content-adaptive bitstream-layer model for coding distortion assessment of H.264/AVC networked video

Bitstream-layer models are designed to use the information extracted from both packet headers and payload for real-time and non-intrusive quality monitoring of networked video. This paper proposes a content-adaptive bitstream-layer (CABL) model for coding distortion assessment of H.264/AVC networked video. Firstly, the fundamental relationship between perceived coding distortion and quantization parameter (QP) is established. Then, considering the fact that the perceived coding distortion of a networked video significantly relies on both the spatial and temporal characteristics of video content, spatial and temporal complexities are incorporated in the proposed model. Assuming that the residuals before Discrete Cosine Transform (DCT) keep to the Laplace distribution, the scale parameters of the Laplace distribution are estimated utilizing QP and quantized coefficients on the basis of the Parseval theorem firstly. Then the spatial complexity is evaluated using QP and the scale parameters. Meanwhile, the temporal complexity is obtained using the weighted motion vectors (MV) considering the variations in temporal masking extent for high motion regions and low motion regions, respectively. Both the two characteristics of video content are extracted from the compressed bitstream without resorting to a complete decoding. Using content related information, the proposed model is able to adapt to different video contents. Experimental results show that the overall performance of CABL model significantly outperforms that of the P.1202.1 model and other coding distortion assessment models in terms of widely used performance criteria, including the Pearson Correlation Coefficient (PCC), the Spearman Rank Order Correlation Coefficient (SROCC), the Root-Mean-Squared Error (RMSE) and the Outlier Ratio (OR).     

Visual‐Attention‐Aware Progressive RoI Trick Mode Streaming in Interactive Panoramic Video Service

In the near future, traditional narrow and fixed viewpoint video services will be replaced by high‐quality panorama video services. This paper proposes a visual‐attention‐aware progressive region of interest (RoI) trick mode streaming service (VA‐PRTS) that prioritizes video data to transmit according to the visual attention and transmits prioritized video data progressively. VA‐PRTS enables the receiver to speed up the time to display without degrading the perceptual quality. For the proposed VA‐PRTS, this paper defines a cutoff visual attention metric algorithm to determine the quality of the encoded video slice based on the capability of visual attention and the progressive streaming method based on the priority of RoI video data. Compared to conventional methods, VA‐PRTS increases the bitrate saving by over 57% and decreases the interactive delay by over 66%, while maintaining a level of perceptual video quality. The experiment results show that the proposed VA‐PRTS improves the quality of the viewer experience for interactive panoramic video streaming services. The development results show that the VA‐PRTS has highly practical real‐field feasibility.     

MULTIGRID METHOD FOR A MODIFIED CURVATURE DRIVEN DIFFUSION MODEL FOR IMAGE INPAINTING

Digital inpainting is a fundamental problem in image processing and many variational models for this problem have appeared recently in the literature. Among them are the very successfully Total Variation （TV） model [11] designed for local inpainting and its improved version for large scale inpainting： the Curvature-Driven Diffusion （CDD） model [10]. For the above two models, their associated Euler Lagrange equations are highly nonlinear partial differential equations. For the TV model there exists a relatively fast and easy to implement fixed point method, so adapting the multigrid method of [24] to here is immediate. For the CDD model however, so far only the well known but usually very slow explicit time marching method has been reported and we explain why the implementation of a fixed point method for the CDD model is not straightforward. Consequently the multigrid method as in [Savage and Chen, Int. J. Comput. Math., 82 （2005）, pp. 1001-1015] will not work here. This fact represents a strong limitation to the range of applications of this model since usually fast solutions are expected. In this paper, we introduce a modification designed to enable a fixed point method to work and to preserve the features of the original CDD model. As a result, a fast and efficient multigrid method is developed for the modified model. Numerical experiments are presented to show the very good performance of the fast algorithm.     

基于方位向相位编码技术的方位向多通道SAR距离模糊抑制方法

距离模糊一直是影响合成孔径雷达(SAR)成像质量的重要因素之一。方位向相位编码(APC)技术是一种有效抑制距离模糊的方法,但是由于APC技术高度依赖于高过采样率,对于多通道SAR系统,APC技术的距离模糊抑制效果很有限。该文提出一种新的基于APC技术的多通道系统距离模糊抑制方法。该方法首先通过APC技术将部分距离模糊信号产生方位平移,通过额外增加接收通道数提供的额外信号自由度,能够在方位向上通过合适的数字波束形成(DBF)技术同时滤去距离模糊和重建方位向信号,因此距离模糊信号可以被很好地抑制。该文最后给出仿真结果,证明该方法的有效性。