Optimal chunk caching in network coding-based qualitative communication

Network processing in the current Internet is at the entirety of the data packet, which is problematic when encountering network congestion. The newly proposed Internet service named Qualitative Communication changes the network processing paradigm to an even finer granularity, namely chunk level, which obsoletes many existing networking policies and schemes, especially the caching algorithms and cache replacement policies that have been extensively explored in Web Caching, Content Delivery Networks (CDN) or Information-Centric Networks (ICN). This paper outlines all the new factors that are brought by random linear network coding-based Qualitative Communication and proves the importance and necessity of considering them. A novel metric is proposed by taking these new factors into consideration. An optimization problem is formulated to maximize the metric value of all retained chunks in the local storage of network nodes under the constraint of storage limit. A cache replacement scheme that obtains the optimal result in a recursive manner is proposed correspondingly. With the help of the introduced intelligent cache replacement algorithm, the performance evaluations show remarkably reduced end-to-end latency compared to the existing schemes in various network scenarios.     

随机均衡器的计算机辅助最优化设计

本文提供了一种实用的随机均衡器的计算机辅助设计方法.以二元件均衡器为链接模型,以非线性最小二乘法为最优化方式,解决了多节均衡器链接中初始参数值的选取问题.讨论了0.618法在非单一极值区间的应用.并且通过实例计算说明这一方法的有效性和实用性.     

基于随机矩阵非渐近谱理论的协作频谱感知算法研究

将随机矩阵的非渐近谱理论应用到协作频谱感知中,对接收信号样本协方差矩阵的最大特征值和最小特征值进行分析,该文提出一种精确的最大最小特征值差(Exact Maximum Minimum Eigenvalue Difference, EMMED)的协作感知算法。对于任意给定的协作用户个数K和采样点数N,首先推导了最大最小特征值之差的精确概率密度函数(Probability Density Function, PDF)和累积分布函数(Cumulative Distribution Function, CDF),然后利用该分布函数设计了所提算法的判决阈值。理论分析表明,EMMED算法的判决阈值较已有的渐进最大最小特征值差(Asymptotic Maximum Minimum Eigenvalue Difference, AMMED)检测更为精确,算法无需主用户信号特征并且能够对抗噪声不确定度影响。仿真结果表明,存在噪声不确定度的感知环境下,EMMED算法较已有的精确最大特征值(Exact Maximum Eigenvalue, EME)和EMMER等频谱感知算法具有更好的检测性能。     

一种用于流水线A/D转换器的低功耗采样/保持电路

文章介绍了一种适用于10位20MS／s流水线A／D转换器的采样／保持（S／H）电路。该电路为开关电容结构，以0．6μm DPDM CMOS工艺实现。采用差分信号输入结构，降低对共模噪声的敏感度，共模反馈电路的设计稳定了共模输出，以达到高精度。该S／H电路采用低功耗运算跨导放大器（OTA），在5V电源电压下，功耗仅为5mW。基于该S／H电路的流水线A／D转换器在20MHz采样率下，信噪比（SNR）为58dB，功耗为49mW。     

Sample selection for visual domain adaptation via sparse coding

Visual domain adaptation has attracted much attention and has made great achievement in recent years. It deals with the problem of distribution divergence between source and target domains. Current methods mostly focus on transforming images from different domains into a common space to minimize the distribution divergence. However, there are many irrelevant source samples for target domain even after the transformation. In order to eliminate the irrelevant samples, we develop a sample selection algorithm using sparse coding theory. We do the sample selection in a common subspace of source and target data to find as many as relevant source samples. In the common subspace, data characteristics are preserved by using graph regularization. Therefore, we can select the most relevant samples for our target image classification task. Moreover, in order to build a discriminative classifier for the target domain, we use not only the common part of source and target domains learned in the common subspace but also the specific part of target domain. The algorithm can be extended to handle samples from multiple source domains. Experimental results show that our visual domain adaptation method on the image classification tasks can be very effective for the state-of-the-art datasets.     

Collagen network as the scaffold for spontaneously distributed optical resonators

The idea behind this work was to acquire one dimensional lasing in the Rhodamine 6G dye doped collagen fibers with the control of random lasing phenomenon properties by changing the dye molecular arrangement. We show that a simple manipulation of the dye concentration in biopolymeric fibril matrix bulk and an additional use of α-cyclodextrin (α-CD) molecules determine formation of specific dye aggregates and as a consequence the shift of the random lasing emission wavelength in the desired direction. The analysis of the light transport mean free path in function of the dye and (α-CD) concentration was done with the use of coherent back scattering technique.     

一种基于RED分组丢弃历史的带宽均衡分配算法

针对目前Internet中的响应流和非响应流带宽分配不均衡的问题,该文提出了一种基于RED分组丢弃历史的算法,该算法可以发现高速率的数据流并对其到达分组按概率作优先丢弃,以避免这些流对带宽的过度占用,多个仿真实验从不同的角度验证了该算法的有效性。     

城域WDM环网及其应用

文章阐述了城域WDM环网的节点结构、保护方式、波长转换器、子速率复用和光网络管理等,给出了WDM环网在城域应用时应考虑的一些因素,并分析了运营商所关心的系统成本问题。     

密码技术中一种随机数检验方法的设计与实现

文章把线性复杂度理论检用于密码技术中,设计一种实用的序列随机性检验方法.该方法可以检测随机序列发生器产生序列的随机性,也可以用于检验密码算法的安全性.通过实验,发现该方法能更全面检验序列的随机特性.     

Image saliency estimation via random walk guided by informativeness and latent signal correlations

Visual saliency is an effective tool for perceptual image processing. In the past decades, many saliency models have been proposed by primarily considering visual cues such as local contrast and global rarity. However, such explicit cues derived only from input stimuli are often insufficient to separate targets from distractors, leading to noisy saliency maps. In fact, the latent cues, especially the latent signal correlations that link visually distinct stimuli (e.g., various parts of a salient target), may also play an important role in saliency estimation. In this paper, we propose a graph-based approach for image saliency estimation by incorporating both explicit visual cues and latent signal correlations. In our approach, the latent correlations between various image patches are first derived according to the statistical prior obtained from 10 million reference images. After that, the informativeness of image patches and their latent correlations are jointly considered to construct a directed graph, on which a random walking process is performed to generate saliency maps that pop-out only the most salient locations. Experimental results show that our approach achieves impressive performances on three public image benchmarks.