Google体系结构分析

为了适应大规模广范围高密度的搜索,Google的网络搜索应用允许在不同的处理器上运行不同的查询;同时,通过对全局索引进行分解,Google也允许在多个处理器上运行单一的查询.Google的主旨是,使用市场上流行的具有通用的PC,以达到大型机所具有的高性能.通过对已有资料进行搜集,对Google的体系结构、工作性能等进行分析,目的是通过对Google的调研,给网格建设提供一定的借鉴.     

New insights on survivability in multi-domain optical networks

With the development of intelligent optical networks and the general multi-protocol label switching (GMPLS) technique, the seamless convergence between IP network and optical network is no longer be a dream but a practical reality. Similar to the Internet, current optical networks have been divided into multiple domains each of which has its own network provider and management policy. Therefore, the development of multi-domain optical networks will be the trend of new-generation intelligent optical networks, and GMPLS-based survivability for multi-domain optical networks will become a hot topic of research in the future. This paper provides a comprehensive review of the existing survivable schemes in multi-domain optical networks and analyzes the shortcomings of current research. Based on previous studies, we present possible challenges and propose new ideas to design efficient survivable schemes to guide the future work of researchers in multi-domain optical networks.     

Locally linear discriminant embedding: An efficient method for face recognition

In this paper an efficient feature extraction method named as locally linear discriminant embedding (LLDE) is proposed for face recognition. It is well known that a point can be linearly reconstructed by its neighbors and the reconstruction weights are under the sum-to-one constraint in the classical locally linear embedding (LLE). So the constrained weights obey an important symmetry: for any particular data point, they are invariant to rotations, rescalings and translations. The latter two are introduced to the proposed method to strengthen the classification ability of the original LLE. The data with different class labels are translated by the corresponding vectors and those belonging to the same class are translated by the same vector. In order to cluster the data with the same label closer, they are also rescaled to some extent. So after translation and rescaling, the discriminability of the data will be improved significantly. The proposed method is compared with some related feature extraction methods such as maximum margin criterion (MMC), as well as other supervised manifold learning-based approaches, for example ensemble unified LLE and linear discriminant analysis (En-ULLELDA), locally linear discriminant analysis (LLDA). Experimental results on Yale and CMU PIE face databases convince us that the proposed method provides a better representation of the class information and obtains much higher recognition accuracies.     

Use of a dark object concept and support vector machines to automate forest cover change analysis

An automated method was developed for mapping forest cover change using satellite remote sensing data sets. This multi-temporal classification method consists of a training data automation (TDA) procedure and uses the advanced support vector machines (SVM) algorithm. The TDA procedure automatically generates training data using input satellite images and existing land cover products. The derived high quality training data allow the SVM to produce reliable forest cover change products. This approach was tested in 19 study areas selected from major forest biomes across the globe. In each area a forest cover change map was produced using a pair of Landsat images acquired around 1990 and 2000. High resolution IKONOS images and independently developed reference data sets were available for evaluating the derived change products in 7 of those areas. The overall accuracy values were over 90% for 5 areas, and were 89.4% and 89.6% for the remaining two areas. The user's and producer's accuracies of the forest loss class were over 80% for all 7 study areas, demonstrating that this method is especially effective for mapping major disturbances with low commission errors. IKONOS images were also available in the remaining 12 study areas but they were either located in non-forest areas or in forest areas that did not experience forest cover change between 1990 and 2000. For those areas the IKONOS images were used to assist visual interpretation of the Landsat images in assessing the derived change products. This visual assessment revealed that for most of those areas the derived change products likely were as reliable as those in the 7 areas where accuracy assessment was conducted. The results also suggest that images acquired during leaf-off seasons should not be used in forest cover change analysis in areas where deciduous forests exist. Being highly automatic and with demonstrated capability to produce reliable change products, the TDA-SVM method should be especially useful for quantifying forest cover change over large areas.     

嵌入式1394总线接口的设计和实现

本文介绍一种嵌入式处理器与1394总线接口设计方法,并给出基于现场可编程门阵列(FPGA)设计的VHDL代码结构、仿真时序和试验结果,最后提出了一种新的通用接口设计方法并指出了它的优势所在.     

基于控制微元的统计自适应增量控制方法

依据系统对模拟量实时控制的要求,提出了基于控制微元的统计自适应增量控制方法,给出了量化控制状态统计图的获取方法,分别找出了扩展控制微元的统计稳定系数、平均统计状态偏差、统计趋势、统计超调、尾偏差等参数与调节增量之问的关系,确定了统计控制策略及其最优化条件,给出了统计预测自适应记忆增量控制器的设计方案.该方法易于微处理器编程,运算速度快,可高效率实现对模拟量的精确控制.     

基于双极偏好控制的多目标粒子群优化算法

考虑双极偏好信息对粒子群的控制作用,提出一种使用双极偏好——正偏好和负偏好引导粒子群向 Pareto 前沿偏好区域进化的方法．根据TOPSIS 决策法思想,将外部种群粒子与正负偏好点的相对贴近度排序作为 外部种群管理和全局最优解更新策略;根据贴近度值确定解集的分布度;选取6 种不同类型的多目标测试函数进行 算法模拟,从世代距离、空间测度和超体积测度3 个指标与基于单极偏好的多目标粒子算法进行性能比较．结果显 示,基于双极偏好控制的多目标粒子群算法的收敛性和综合性能更优秀．     

白蚁提取液急性毒性及致突变性研究

本文采用大,小鼠急性经口毒性试验、Ａｍｅｓ试验、小鼠骨髓细胞微核试验及小鼠精子畸变试验对白蚁提取液的毒理学安全性进行了研究,结果表明,白蚁提取液大,小鼠急性经口ＬＤ５０均大于１０ｇ／ｋｇ体重,属“实际无毒”：体内（包括体细胞和生殖细胞）、体外致突变性试验系统均未检出其致突性。     

Modelling the removal of organic vehicle from ceramic or metal mouldings: The effect of gas permeation on the incidence of defects

A shrinking undegraded core and a porous outer layer result, if the organic vehicle used for shaping ceramic or metal powder mouldings recedes in the interparticle space of the moulded body during pyrolysis. In the present work, a numerical model has been used which simulates the undegraded shrinking core situation and quantifies degradation of the organic vehicle and the diffusion of the resulting products in solution in the organic phase during pyrolysis of a ceramic moulding. This model is extended to include gaseous mass transport in the porous outer layer for a moulding in the shape of an infinite cylinder. The effect of resistance to gaseous mass transport in the porous outer region on defects originating in inner regions was estimated. It is shown that the greatest obstruction to mass transport is diffusion of degradation products in solution in the organic phase. However, the permeability coefficient for gas transport in the outer region begins to affect the critical heating rate required for avoidance of defects only when it is less than 10^–15m².Nomenclature C Concentration,C=C (r, t), based on the total volume of ceramic suspension - d Effective molecular diameter of alphamethylstyrene - D Diffusion coefficient,D=D (C, T) - e Porosity of powder - E Activation energy for thermal degradation - h Remaining weight fraction of polymer - H_vap Enthalphy of vaporization - i Node number - I Pre-exponential constant in Equation 13 - j Time step - K _p Permeability coefficient - K ₀ Specific rate constant - m Mass of monomer displaced - M Mass of one alphamethylstyrene molecule - P Monomer vapour pressure - P _s Monomer vapour pressure at outer surface of the cylinder - P ₁ ⁰ Vapour pressure of monomer over its pure liquid - Q Rate of production of monomer, based on the total volume of ceramic suspension - r Radius of the cylinder - r _j Distance from central axis to the inner surface of the porous layer at time stepj - r ₀ Initial radius of the cylinder - R Universal gas constant - S ₀ Specific surface area of powder per unit solid volume - t Time - T Absolute temperature - T _c Temperature at maximum vapour pressure of monomer and atZ _c - V Volume of monomer - V _c Ceramic volume fraction - V _p Polymer volume fraction - w Mass of monomer stored in the porous annulus - Z Heating rate - Z _c Critical heating rate - ₁ Volume fraction of monomer in the polymer-monomer solution - Viscosity of the monomer vapour - _p Density of the polymer - Polymer-monomer interaction constant     

Single-Atom Metal Sites Anchored Hydrogen-Bonded Organic Frameworks for Superior “Two-In-One” Photocatalytic Reaction

Photoredox catalysis is a green solution for organics transformation and CO₂ conversion into valuable fuels, meeting the challenges of sustainable energy and environmental concerns. However, the regulation of single-atomic active sites in organic framework not only influences the photoredox performance, but also limits the understanding of the relationship for photocatalytic selective organic conversion with CO₂ valorization into one reaction system. As a prototype, different single-atomic metal (M) sites (M²⁺ = Fe²⁺, Co²⁺, Ni²⁺, Cu²⁺, and Zn²⁺) in hydrogen-bonded organic frameworks (M-HOF) backbone with bridging structure of metal-nitrogen are constructed by a typical “two-in-one” strategy for superior photocatalytic C N coupling reactions integrated with CO₂ valorization. Remarkably, Zn-HOF achieves 100% conversion of benzylamine oxidative coupling reactions, 91% selectivity of N-benzylidenebenzylamine and CO₂ conversion in one photoredox cycle. From X-ray absorption fine structure analysis and density functional theory calculations, the superior photocatalytic performance is attributed to synergic effect of atomically dispersed metal sites and HOF host, decreasing the reaction energy barriers, enhancing CO₂ adsorption and forming benzylcarbamic acid intermediate to promote the redox recycle. This work not only affords the rational design strategy of single-atom active sites in functional HOF, but also facilitates the fundamental insights upon the mechanism of versatile photoredox coupling reaction systems.