基于WinCE的电梯监控系统多串口通信实现

提出了一种基于WinCE的多串口电梯远程监控系统的实现方法.该方法以S3C2440微处理器为核心构建硬件平台,实现了与其他设备的串口通信;同时以WinCE5.0为软件平台,完成多串口分层流驱动的设计.通过文件映射,解决了访问多串口设备时产生的竞态问题.测试结果表明,该系统通信正常、数据稳定,能充分满足电梯监控对串行通信的要求.     

复杂产品虚拟样机协同开发平台设计与实现

提出复杂产品虚拟样机协同开发平台的体系结构和功能框架,设计统一数据访问接口,自主开发了“复杂产品虚拟样机协同开发平台”软件。该软件包括个人工作空间管理、仿真建模、数据管理、过程管理、模型库管理和仿真评估等功能模块,能够支持复杂产品从设计、仿真、分析和优化的整个多学科协同开发过程,实现了对协同开发相关的项目、人员、模型、数据和工作流等资源的集成化管理,为复杂产品虚拟样机的实施提供了设计、仿真和资源管理的分布式支撑环境。     

混合式P2P系统中基于缓存的多项查询方法研究

首先从混合式P2P网络拓扑结构出发,结合DHT思想,提出了基于DHT的层次化P2P网络模型.其次根据在文档集巨大的情况下,用户提交的查询不可能"面面俱到",实际用来回答查询的文档仅仅是文档集中很小的一部分这一思想,在层次化P2P模型的超级节点中建立了分布式缓存,运用分布式索引与缓存技术,提出一种新的方法来解决多项查询问题.即由多项查询中的某个关键字key,根据hash函数定位到负责该key的超级节点,查询该节点上的分布式索引得到缓存具体存储位置,最终将结果返回给用户,如若缓存中没有所要查询的内容,则广播该查询,同时根据系统中的历史广播查询信息来计算某个待选缓存项的利益值,利益最大的待选项加入缓存.一般针对多项查询的泛洪算法往往会造成巨大的网络信息量,提出的方法牺牲了超级节点上一小部分的存储力,缓解了多项查询造成的网络拥挤现象.同时,基于DHT的层次化P2P模型也具有很好的稳定性,不会因为大量节点的动态加入或者退出而无法进行多项查询.     

Identify Congested Links Based on Enlarged State Space

When paths share a common congested link, they will all suffer from a performance degradation. Boolean tomography exploits these performance-level correlations between different paths to identify the congested links. It is clear that the congestion of a path will be distinctly intensive when it traverses multiple congested links. We adopt an enlarged state space model to mirror different congestion levels and employ a system of integer equations, instead of Boolean equations, to describe relationships between the path states and the link states. We recast the problem of identifying congested links into a constraint optimization problem, including Boolean tomography as a special case. For a logical tree, we propose an up-to-bottom algorithm and prove that it always achieves a solution to the problem. Compared with existing algorithms, the simulation results show that our proposed algorithm achieves a higher detection rate while keeping a low false positive rate.     

Subspace-based continuous-time identification of fractional order systems from non-uniformly sampled data

This work focuses on the identification of fractional commensurate order systems from non-uniformly sampled data. A novel scheme is proposed to solve such problem. In this scheme, the non-uniformly sampled data are first complemented by using fractional Laguerre generating functions. Then, the multivariable output error state space method is employed to identify the relevant system parameters. Moreover, an in-depth property analysis of the proposed scheme is provided. A numerical example is investigated to illustrate the effectiveness of the proposed method.     

Optimization of program recursive function calls analysis method

Static analysis can be classified into intra-procedural analysis and inter-procedural analysis-by-analysis objects. Inter-procedural analysis need to analyze the whole program adopting bottom-up parsing algorithms. Inter-procedural analysis can be converted to intra-procedural analysis by logging the context of follower’s function call in bottom-up analysis. However, the existence of recursive function calls in program increases the difficulty of inter-procedural analysis, which affects the detection accuracy of static analysis to some extent. An optimal method for analyzing the recursive function calls of program is presented in this paper. This method can lift the recursive function calls in function call graph of the program to be analyzed on the premise that vital function calls will be preserved. In this way, the false negative rate and false positive rate of program static analysis can be reduced and the accuracy of program security check can be improved.     

Appearance Harmonization for Single Image Shadow Removal

Shadow removal is a challenging problem and previous approaches often produce de‐shadowed regions that are visually inconsistent with the rest of the image. We propose an automatic shadow region harmonization approach that makes the appearance of a de‐shadowed region (produced using any previous technique) compatible with the rest of the image. We use a shadow‐guided patch‐based image synthesis approach that reconstructs the shadow region using patches sampled from non‐shadowed regions. This result is then refined based on the reconstruction confidence to handle unique textures. Qualitative comparisons over a wide range of images, and a quantitative evaluation on a benchmark dataset show that our technique significantly improves upon the state‐of‐the‐art.     

Single Criterion Net Flow Using Concordance and Discordance Relations

This article proposes a flow-based method using the single criterion net flow for pattern classification. Traditional single criterion net flow, generated on the basis of net partial concordance indices, measures the preference intensity for one pattern with respect to all others on this criterion. A concordance index measures the intensity of preference for one pattern over another pattern. Contrary to traditional flow-based methods, such as PROMETHEE, in which only the concordance relation is taken into account, the proposed method proposes a new definition of single criterion net flow using both concordance and discordance relations. This can balance pros and cons for the preference of one pattern over another pattern for a criterion. The final classification decision for a new pattern depends on its net flow. Criteria weights are determined using a genetic-algorithm-based approach. Empirical results involving bankruptcy prediction demonstrate that the proposed method performs well compared to other well-known classification methods.