基于二次剩余的低功耗蓝牙用户认证方案

针对低功耗蓝牙协议栈安全机制中缺乏用户身份合法性认证的问题,首先分析并指出了已有蓝牙用户认证协议无法抵抗假冒和窃听攻击,且无法适用于低功耗蓝牙协议;其次结合低功耗蓝牙协议层次设计了用户认证模型,构建了基于二次剩余的低功耗蓝牙用户认证方案。通过中国剩余定理求解二次剩余,完成用户身份双向认证,同时满足用户匿名要求。安全性分析表明方案可以有效地抵御用户口令泄露、从设备丢失、假冒及窃取用户隐私等攻击方式。理论分析及实验结果表明具有较高的计算效率和较小的存储开销,适用于资源受限的低功耗蓝牙可穿戴设备应用场景。     

Graphs in Scientific Visualization: A Survey

Graphs represent general node‐link diagrams and have long been utilized in scientific visualization for data organization and management. However, using graphs as a visual representation and interface for navigating and exploring scientific data sets has a much shorter history, yet the amount of work along this direction is clearly on the rise in recent years. In this paper, we take a holistic perspective and survey graph‐based representations and techniques for scientific visualization. Specifically, we classify these representations and techniques into four categories, namely partition‐wise, relationship‐wise, structure‐wise and provenance‐wise. We survey related publications in each category, explaining the roles of graphs in related work and highlighting their similarities and differences. At the end, we reexamine these related publications following the graph‐based visualization pipeline. We also point out research trends and remaining challenges in graph‐based representations and techniques for scientific visualization.     

Visualizing Group Structures in Graphs: A Survey

Graph visualizations encode relationships between objects. Abstracting the objects into group structures provides an overview of the data. Groups can be disjoint or overlapping, and might be organized hierarchically. However, the underlying graph still needs to be represented for analyzing the data in more depth. This work surveys research in visualizing group structures as part of graph diagrams. A particular focus is the explicit visual encoding of groups, rather than only using graph layout to indicate groups implicitly. We introduce a taxonomy of visualization techniques structuring the field into four main categories: visual node attributes vary properties of the node representation to encode the grouping, juxtaposed approaches use two separate visualizations, superimposed techniques work with two aligned visual layers, and embedded visualizations tightly integrate group and graph representation. The derived taxonomies for group structure and visualization types are also applied to group visualizations of edges. We survey group‐only, group–node, group–edge and group–network tasks that are described in the literature as use cases of group visualizations. We discuss results from evaluations of existing visualization techniques as well as main areas of application. Finally, we report future challenges based on interviews we conducted with leading researchers of the field.     

Smart Spaces for Adaptive Information Integration in Bioinformatics

Bioinformatics is reaping the benefits of advances in Semantic Web technology thanks to the growing number of available biomedical web resources and portals. Although positive in general, this abundance poses practical challenges to researchers who must be skilled in techniques for retrieving and integrating sparse and complex contents, and thereof calls for more “intelligent” and user friendly ways of interaction to easily get information. With the aim of making available the intelligent functionality of smart systems, this paper presents SSAIIB (Smart Spaces for Adaptive Information Integration in Bioinformatics), a reference framework for designing bioinformatics smart applications that support discovering, aggregating and delivering contents from web resources according to user’s goals, tasks and concerns. The “Smart Spaces” are software environments whose smartness lies in their ability to adaptively accomplish specific user’s activities such as the exploiting content from biomedical resources, integrating data captured from different sources, supporting data analytics, etc. SSAIIB is structured around two main technologies: service oriented architectures and software agents. In particular, it relies on mechanisms for dynamically assembling suitable services and the use of agents as a natural metaphor for both modelling user’s activities and accessing web resources. A case study is presented that shows the application of SSAIIB to the design and the implementation of a smart space for annotating biomedical texts.     

Converging coolness and investigating its relation to user experience

Recently a number of studies appeared that operationalised coolness and explored its relation to digital products. Literature suggests that perceived coolness is another factor of user experience, and this adds to an existing explosion of dimensions related to aesthetics, hedonic quality, pragmatic quality, attractiveness, etc. A critical challenge highlighted in prior research is to study the relationships among those factors and so far, no studies have empirically examined the relationship between coolness and other established user experience factors. In this paper, we address this challenge by presenting two studies one that focuses on factors from two cool questionnaires, and one that compares them against existing User eXperience (UX) factors. Our findings show that factors from the two cool questionnaires converge and they also converge to existing, established UX factors. Thus, 11 distinct cool and UX factors converge into 5 for the case of mobile devices. Our findings are important for researchers, as we demonstrate through a validated model that coolness is part of UX research, as well as for practitioners, by developing a questionnaire that can reliably measure both perceived inner and outer coolness as well as the overall coolness judgement based on 5 factors and 21 items.     

A Twofold Strategy for Riparian Restoration: Combining a Functional Flow Regime and Direct Seeding to Re‐establish Cottonwoods

The transboundary St Mary River drains Glacier National Park, USA, and was progressively dammed and diverted over the 20th century to support agricultural irrigation in northern Montana and southern Alberta, Canada. Following reduced instream flows, the riparian cottonwoods collapsed, and by 2000, few parental trees remained to provide seeds for cottonwood replenishment. As a novel twofold restoration strategy we: (1) worked with the dam operators to deliver a functional flow regime, a regulated instream flow pattern intended to recover some ecological function and specifically seedling recruitment, and (2) delivered cottonwood seeds by direct spreading and by sticking cuttings with seed catkins to allow gradual seed dispersal. The combination of river regulation and seeding enabled cottonwood colonization, and around 1.5% of the applied seeds produced seedlings after the first summer, at sites without livestock or heavy recreational use. Around 15% of those seedlings survived through the fourth summer, with mortality due to drought stress and flood scour, and establishment and survival were higher for the prairie cottonwood, Populus deltoides, than the narrowleaf cottonwood, Populus angustifolia. This study confirmed that the lack of seed source trees limited cottonwood colonization and demonstrated that the twofold restoration strategy provides promise for severe situations where parental trees have been lost. However, this would require substantial effort, and it would be more efficient to provide survivable instream flow patterns that avoid cottonwood collapse. Copyright © 2015 John Wiley & Sons, Ltd.     

再生水利用激励机制研究

针对我国再生水事业推进缓慢、再生水利用激励措施不健全等突出问题,初步探析了我国再生水利用激励机制的基本框架,系统地阐述了该机制的激励理论和建立过程。再生水利用激励机制是一种政府作为激励主体,对从事再生水生产的企业和用户产生激励作用的框架体系。通过对激励过程理论、马斯洛需求层次理论的分析,指出了当前再生水利用不同主体在激励过程面临的障碍,结合激励机制理论和环境经济学原理,提出了促进再生水利用经济外部性内部化的主要途径和激励手段。再生水利用激励机制将政府、再生水企业、用户有效地结合起来,妥善处理其中的利益关系,从而推动我国再生水市场健康发展。     

一种用户偏好的美学图像推荐方法

在众多的图像信息资源中快速、有效地寻找用户最喜欢的图像,提出了一种用户偏好的美学图像推荐方法,通过使用深度卷积神经网络提取图像的深层特征,并经过SVMrank后得到一个图像排序得分,同时使用手工标记的图像美学因素（如色调法、图像组合规则、清晰度以及简洁性）计算并得到图像的美学特征,得到一个美学得分,最后进行加权交叉验证得到一个令用户满意的推荐结果。通过实验表明该算法为一种有效的美学偏好推荐方法。     

基于迭代攻击检测的联合压缩频谱感知算法

针对宽带认知无线电网络中频谱感知所需采样率过高以及频谱感知性能容易受到模仿主用户攻击威胁的问题,提出了基于迭代攻击检测的联合压缩频谱感知算法。认知无线电用户利用压缩感知理论降低信号的采样率,并将感知结果报告给融合中心。融合中心利用来自各认知无线电用户的感知报告估计主用户发射信号功率和路径损失参数,根据估计误差得到测量剩余值。在迭代攻击检测中,通过比较测量剩余值发现和去除受到模仿主用户攻击影响的异常感知报告,合并剩余报告得到可靠的联合频谱感知结果。仿真表明,该算法能够有效抵抗模仿主用户攻击,并且能够以低于奈奎斯特准则的采样率实现准确可靠的频谱感知。     

基于Hive的海量搜索日志分析系统研究

针对传统分布式模型在海量日志并行处理时的可扩展性和并行程序编写困难的问题, 提出了基于Hive的Web海量搜索日志分析机制。利用HQL语言以及Hadoop分布式文件系统(HDFS)和MapReduce编程模式对海量搜索日志进行分析处理, 对用户搜索行为进行了分析研究。对用户搜索行为中的查询热点主题、用户点击数和URL排名、查询会话的分析结果对于搜索引擎的排序算法和系统优化都有一定的指导意义。