Know by a handful the whole sack: efficient sampling for top-k influential user identification in large graphs

Influence Maximization aims to find the top-K influential individuals to maximize the influence spread within a social network, which remains an important yet challenging problem. Most existing greedy algorithms mainly focus on computing the exact influence spread, leading to low computational efficiency and limiting their application to real-world social networks. While in this paper we show that through supervised sampling, we can efficiently estimate the influence spread at only negligible cost of precision, thus significantly reducing the execution time. Motivated by this, we propose ESMCE, a power-law exponent supervised Monte Carlo estimation method. In particular, ESMCE exploits the power-law exponent of the social network to guide the sampling, and employs multiple iterative steps to guarantee the estimation accuracy. Moreover, ESMCE shows excellent scalability and well suits large-scale social networks. Extensive experiments on six real-world social networks demonstrate that, compared with state-of-the-art greedy algorithms, ESMCE is able to achieve almost two orders of magnitude speedup in execution time with only negligible error (2.21 % on average) in influence spread.     

Preparation of phenolic resin derived 3-D ordered macroporous carbon

Three-dimensionally ordered long-range macroporous carbon structures were prepared using commercially available phenolic resin by utilizing sacrificial colloidal silica crystalline arrays as templates that were subsequently removed by HF etching after pyrolysis in an argon atmosphere. SEM, TEM, and BET were employed to characterize the morphology and the surface area of the porous carbon structures. The pore size (150–1000 nm) and BET surface area, which reflect pore volume (298.6 m²/g (1.32 cm³/g) ∼ 93.7 m²/g (0.12 cm³/g)), of the macroporous carbon structures produced were approximately proportional to the size (150–1000 nm) of the sacrificial silica sphere templates used (annealing temp. 550°C). The achieved 550 nm porous carbon structures were examined to function as potential catalyst carriers and were successfully impregnated with Ag or Pt-Ru on their inner walls after borohydride reduction at room temperature. In addition, porous carbon patterns were fabricated using the ‘micromolding in capillary’ technique, which has potential applications in the microreaction technology.     

网络边布局技术研究综述

网络边布局技术是网络可视化研究的重要内容,良好的边布局能够有效地展示网络的整体结构并从中揭示出某些隐含的信息模式.为了全面地总结和分析现有网络边布局技术,首先归纳了网络边布局的主要任务,回顾了指导网络边布局的美学标准.然后将网络边布局技术归纳为3类:边路由技术、边融合技术和边集束技术,分别阐述了各类技术中典型布局方法的主要原理和特征,并重点对边集束技术进行了分类分析.最后总结了目前研究中还存在的一些问题,展望了网络边布局技术的发展前景和面临的挑战,以期为相关领域的研究者提供有益参考.     

Preparation of three-dimensional ordered macroporous SiCN ceramic using sacrificing template method

Three-dimensional (3D) long range well ordered macroporous SiCN ceramics were prepared by infiltrating sacrificial colloidal silica templates with the low molecular weight preceramic polymer, polysilazane. This was followed by a thermal curing step, pyrolysis at 1250 °C in a N₂ atmosphere, and finally the removal of the templates by etching with dilute HF. The produced macroporous SiCN ceramics showed high BET surface areas (pore volume) in the range 455 m²/g (0.31 cm³/g)–250 m²/g (0.16 cm³/g) with the pore sizes of 98–578 nm, which could be tailored by controlling the sizes of the sacrificial silica spheres in the range 112–650 nm. The sphere-inversed macropores were interconnected by 50 ± 30 nm windows and 3–5 nm mesopores embedded in the porous SiCN ceramic frameworks, which resulted in a trimodal pore size distribution. The surface of the achieved porous SiCN ceramic was then modified by Pt–Ru nanoparticle depositing under mild chemical conditions.     

Dynamic surface control of a piezoelectric fuel injector during rate shaping

Fuel injection rate shaping is a strategy to improve fuel efficiency and reduce harmful emissions in diesel engines. Due to their fast response, piezoelectric fuel injectors are capable of rate shaping operation. This paper describes a model-based closed-loop controller of injection flow rate for a piezoelectric fuel injector. This within-an-engine-cycle control strategy utilizes a dynamic surface control scheme and shows an injection flow rate tracking capability. Practical issues with LabVIEW FPGA control implementation are also addressed. The performance of the controller is verified with simulation and experimental results at different rail pressures and desired injection rates. The experiments show a maximum error of total fuel per one injection event of 2.5%. A stability analysis is also included.     

一种应用干扰消除进行冲突消解的分布式无线MAC协议

媒介接入控制(MAC)用以协调无线节点对公共信道的共享,对无线网络性能有至关重要的影响。传统的MAC协议只能抑制冲突,不能根除及处理冲突。提出了一种基于已知干扰消除技术的新型消解冲突方法,并以此为基础设计了一个全新的MAC协议——CR-MAC。在CR-MAC协议中,无线接入点(AP)通过将部分报文传输与已知干扰消除相结合来解码冲突所包含的所有报文。因此发生冲突的报文传输过程能够被充分利用,且所需的报文重传减少了。实验结果表明,在网络吞吐率及预期报文时延指标上,CR-MAC协议较普遍采用的IEEE 802.11DCF协议均有明显优势。     

面向自主Web服务的态势信息监视模型及其实现技术

为了应对互联网环境的开放性和动态性,需要加强传统服务的自主性并对其服务态势状况进行有效监视和管理,从而为自主Web服务的灵活应用以及适应调整提供有效支持。在传统的SOA架构基础之上,对Web服务进行了自主化扩展,提出了自主Web服务的态势模型及其监视架构,设计和实现了相应的软件平台,并开展了案例分析来验证模型和实现技术的可行性。     

基于Fisher字典学习稀疏表示的高光谱图像分类

近年基于稀疏表示的分类框架(Sparse Representation based Classification,SRC)在计算机视觉和模式识别领域取得了巨大成功,高光谱图像解译也逐渐引入稀疏表示方法。针对基于SRC的高光谱图像分类算法随机抽取训练样本构成字典较难捕获相似类别的相对差异性信息问题,提出采用Fisher字典学习方法增强相似类训练样本的可区分性。此外,考虑到高光谱图像具有较强空间相关性的特点,设计一种简单有效的投票策略进行类别判决。大量实验表明:基于Fisher字典学习的联合投票分类方法能够较好地改善高光谱分类精度。     

Processing and characterization of particles reinforced SiOC composites via pyrolysis of polysiloxane with SiC or/and Al fillers

Polysiloxane loaded with SiC as inert filler, and Al as active filler, was pyrolyzed in nitrogen to fabricate SiOC composites, and the processing and properties of the filled SiOC composites were investigated. Adding SiC fillers could reduce the linear shrinkage of filler-free cured polysiloxane in order to obtain monolithic SiC/SiOC composites. The flexural strength of SiC/SiOC composites reached 201.3 MPa at a SiC filler content of 27.6 vol.%. However, SiC/SiOC composites exhibited poor oxidation resistance, thermal shock resistance and high temperature resistance. Al fillers could react with hydrocarbon generated during polysiloxane pyrolysis at 600 °C and N₂ at 800 °C to form Al₄C₃ and AlN, respectively. The volume expansions resulting from these two reactions were in favor of the reduction in linear shrinkage and the improvement in flexural strength of SiC/SiOC composites. The flexural strength of Al-containing SiC/SiOC composites was 1.36 times that of SiC/SiOC composites without Al at an Al filler content of 20 vol.%. The addition of Al fillers remarkably improved the high temperature resistance and oxidation resistance of SiC/SiOC composites, but not thermal shock resistance.