二次B-Spline时域基函数的TDFEM的应用

提出了时域有限元法(TDFEM)的一种新的基函数—二次B-spline时域基函数.首先简述了时域有限元法的原理和基本公式;然后提出了新型的基于B-spline函数的条件稳定和无条件稳定的时域有限元法方案,并应用于三维电磁辐射问题.通过典型的算例对这两种方案的精度、运算时间进行了比较,证实了基于二次B-spline函数的时域有限元法的有效性.通过稳定性理论分析得出该算法的精确稳定性,并且通过数值计算的结果得到验证.     

行为时序逻辑中公平性的研究与完善

基于行为时序逻辑(TLA)的并发系统描述,就是对系统的初始状态、系统行为和行为的公平性进行规约和描述,但TLA中的公平性具有局限性,无法准确地描述某些系统的行为,从而限制了TLA的描述能力。通过研究TLA中公平性的推导过程,分析公平性的概念与定义方法,并以实际例子说明它的局限性。在此基础上,提出以加入两级新的公平性方式对其进行完善。最后,证明了新公平性等级之间的蕴涵关系。完善后的公平性具有更强的描述能力,能够对系统进行更完整的描述与规约。     

Variability of complementary relationship and its mechanism on different time scales

In the complementary relationship (CR) between actual and potential evapotranspiration, wet envi- ronment evapotranspiration (Ew) is usually calculated using the Priestley-Taylor (P-T) equation. Based on the data obtained from 38 catchments of the Haihe River basin and the Weishan experiment site in Shandong Province of China, this study has found variations in the Priestley-Taylor parameter α (e.g. increase in values with increase in the amount of precipitation on annual scale, seasonal fluctuation noted t...     

任务级行动序列问题中的定性偏好研究

关注了一类典型行动序列,研究如何在动作集合上存在定性偏好,且偏好集合存在不一致性时开展规划。所考虑的行动序列问题称为任务级COA,以抽象层次的动作为基本要素,所考虑的定性偏好包括静态偏好和时序偏好,所讨论的规划目的是获得最大满意度的COA方案。首先建立了偏好与约束的归一化形式描述,在此基础上形成了COA方案设计算法;进一步,使用计算辩论技术排除偏好集合中的不一致性,形成用户接受度最高的COA方案。文中建立的以定性推理为基础的规划框架,实现了偏好解耦,能够适应不同的领域问题,是以定量计算为基础的传统规划算法的有效补充。通过快速响应卫星成像的COA案例,演示了算法的可行性。     

Temporal evolution of contacts and communities in networks of face-to-face human interactions

Temporal dynamics of social interaction networks as well as the analysis of communities are key aspects to gain a better understanding of the involved processes, important influence factors, their effects, and their structural implications. In this article, we analyze temporal dynamics of contacts and the evolution of communities in networks of face-to-face proximity. As our application context, we consider four scientific coil- ferences. On a structural level, we focus on static and dynamic properties of the contact graphs. Also, we analyze the resulting community structure using state-of-the-art automatic community detection algorithms. Specifically, we analyze tile evolution of contacts and communities over time to consider the stability of the respective conmmnities. Furthermore, we assess different factors which have an influence on the quality of com- munity prediction. Overall, we provide first important insights into the evolution of contacts and communities in face-to-face contact networks.     

Towards evolvable Internet architecture-design constraints and models analysis

There is a general consensus about the success of Internet architecture in academia and industry. However, with the development of diversified application, the existing Internet architecture is facing more and more challenges in scalability, security, mobility and performance. A novel evolvable Internet architecture framework is proposed in this paper to meet the continuous changing application requirements. The basic idea of evolvability is relaxing the constraints that limit the development of the architecture while adhering to the core design principles of the Internet. Three important design constraints used to ensure the construction of the evolvable architecture, including the evolvability constraint, the economic adaptability constraint and the manageability constraint, are comprehensively described. We consider that the evolvable architecture can be developed from the network layer under these design constraints. What＇s more, we believe that the address system is the foundation of the Internet. Therefore, we propose a general address platform which provides a more open and efficient network environment for the research and development of the evolvable architecture.     

融合视觉风格和标签约束的少数民族服装图像解析

目的 少数民族服装款式结构复杂,视觉风格各异。由于缺少民族服装语义标签、局部特征繁杂以及语义标签之间存在相互干扰等因素导致少数民族服装图像解析准确率和精度较低。因此,本文提出了一种融合视觉风格和标签约束的少数民族服装图像解析方法。方法 首先基于本文构建的包含55个少数民族的服装图像数据集,按照基本款式结构、着装区域、配饰和不同视觉风格自定义少数民族服装的通用语义标签和民族语义标签,同时设置4组标注对,共8个标注点;然后,结合自定义语义标签和带有标注对的训练图像,在深度完全卷积神经网络SegNet中加入视觉风格以融合局部特征和全局特征,并引入属性预测、风格预测和三元组损失函数对输入的待解析图像进行初步解析;最后,通过构建的标签约束网络进一步优化初步解析结果,避免标签相互干扰,得到优化后的最终解析结果。结果 在构建的少数民族服装图像数据集上进行验证,实验结果表明,标注对有效提升了局部特征的检测准确率,构建的视觉风格网络能够有效融合少数民族服装的全局特征和局部特征,标签约束网络解决了标签之间相互干扰的问题,在结合视觉风格网络和标签约束网络后,能够明显提升少数民族服装解析的平均精度,像素准确度达到了90.54%。结论 本文提出的融合视觉风格和标签约束的少数民族服装图像解析方法,能够提高少数民族服装图像解析的准确率和精度,对传承祖国文化、保护非物质文化遗产具有很好的意义。     

Two-stage stochastic minimum cost consensus models with asymmetric adjustment costs

When dealing with consensus cost problems with asymmetric adjustment costs, the uncertain scenarios with certain probabilities which are becoming a serious problem decision-makers have to face. However, existing optimization-based consensus models have failed to consider uncertain factors that could influence the final consensus and total consensus cost. In order to better deal with these issues, it is necessary to develop practical consensus optimal models. Thus, we establish three two-stage stochastic minimum cost consensus models with asymmetric adjustment costs that may eventually lead the way to better consensus outcomes. The impact of uncertain parameters (such as individual opinions, unit asymmetric adjustment costs, compromise limits, cost-free thresholds) are investigated by modeling three kinds of uncertain consensus models. We solve the proposed two-stage stochastic consensus problem iteratively using the L-shaped algorithm and show the convergence of the algorithm. Furthermore, a case of pollution control negotiations verifies the practicability of the proposed models. Moreover, the comparison of results with the L-shaped algorithm and CPLEX shows that the L-shaped algorithm is more effective in solving time. Some discussions and comparisons on local and global sensitivity analysis of the uncertain parameters are presented to reveal the features of the proposed models. Finally, the relationships between the minimum cost consensus model and minimum cost consensus models with asymmetric adjustment costs and the proposed models are also provided.     

一种考虑电压岛边界约束的多电压布图算法

多电压设计(multiple supply voltage,MSV)是降低SoC功耗的有效方法之一.为便于电压岛供电引脚的放置,提出了一种考虑电压岛边界约束的多电压布图算法.首先,基于切分树表示的布图解特点,提出一种边界检查算法快速确定所有模块的边界信息.其次,以优化功耗为目标采用改进动态规划方法进行多电压分配并构建电压岛.最后,以模拟退火算法作为搜索引擎对芯片的面积、线长和功耗进行协同优化.为减少SA迭代次数,采用了一个两阶段的降温策略.对GSRC电路的实验结果表明,该算法可获得满足边界约束的多电压布图,且和不考虑边界约束时相比,仅在功耗上平均增加5.2％.     

车牌图像色彩迁移与正则化约束去雾算法

针对雾天车牌图像模糊、车牌识别率低的问题,给出了车牌图像色彩迁移与正则化约束去雾算法。算法主要包含色彩迁移去雾和文本修复两个模块。采用MKL（Monge-Kantorovitch Linear Colour Mapping）色彩迁移算法,恢复雾天车牌颜色信息实现去雾;利用车牌的文本像素的强度和梯度特征对车牌图像进行正则化约束,实现车牌中文本的修复。实验结果表明,无论针对合成车牌雾图还是自然车牌雾图,去雾效果良好,且在薄雾、中等雾及浓雾三种不同雾度环境下都能够有效提高车牌识别率。