A formal model for the interoperability of service clouds

Large-scale service-oriented computing is based on the idea that services from various servers are combined into one distributed application. Referring to a collection of services on one server as a ??service cloud??, the problem investigated in this paper is to define formal high-level specifications of such distributed applications and to enable the location of suitable services for them. Based on the language-independent model of Abstract State Services (AS²s), which serves as a universal integrated model for data and software as services, we extend AS²s by high-level action schemes called ??plots?? as a means to specify permitted sequences of service operations. On these grounds, we develop a model for service mediators, that is, specifications of composed services in which service slots have to be filled by actual services, and investigate matching conditions for slots of mediators and services. For a services to match a slot in a mediator, a (generalised) projection of the mediator must comply with the plot of the service. Furthermore, the service must be semantically adequate, which requires the use of a service ontology.     

主机数据流量检测的实现

分布式网络环境中主机数据流量的异常通常反映出主机是否遭受病毒、木马等恶意程序的入侵而成为网络攻击中的傀儡机,因此,对主机数据流量进行监测可以尽早发现潜在的危险。研究了基于Cisco路由器的主机数据流量检测的基本方法,并给出了具体的程序实现方法和网络硬件环境配置方法。     

A new parallel particle filter face tracking method based on heterogeneous system

This paper proposed a multi-cue-based face-tracking algorithm with the supporting framework using parallel multi-core and one Graphic Processing Unit (GPU). Due to illumination and partial-occlusion problems, face tracking usually cannot stably work based on a single cue. Focusing on the above-mentioned problems, we first combined three different visual cues??color histogram, edge orientation histogram, and wavelet feature??under the framework of particle filters to considerably improve tracking performance. Furthermore, an online updating strategy made the algorithm adaptive to illumination changes and slight face rotations. Subsequently, attempting two parallel approaches resulted in real-time responses. However, the computational efficiency decreased considerably with the increase of particles and visual cues. In order to handle the large amount of computation costs resulting from the introduced multi-cue strategy, we explored two parallel computing techniques to speed up the tracking process, especially the most computation-intensive observational steps. One is a multi-core-based parallel algorithm with a MapReduce thread model, and the other is a GPU-based speedup approach. The GPU-based technique uses features-matching and particle weight computations, which have been put into the GPU kernel. The results demonstrate that the proposed face-tracking algorithm can work robustly with cluttered backgrounds and differing illuminations; the multi-core parallel scheme can increase the speed by 2?C6 times compared with that of the corresponding sequential algorithms. Furthermore, a GPU parallel scheme and co-processing scheme can achieve a greater increase in speed (8×?C12×) compared with the corresponding sequential algorithms.     

Prediction mode modulated data-hiding algorithm for H.264/AVC

In this paper, a data-hiding algorithm with large data payload for H.264/AVC is proposed. The secret information is embedded by modulating the prediction modes of 4?×?4 luminance blocks. If the best mode does not match the information bit, the prediction mode should be modulated by replacing the best mode with the substitute mode. The substitute mode is the one with the least Lagrangian cost among those having different parity with the best mode. Due to high secrecy and easy reproducibility of chaos, the secret information is first encrypted by a chaotic sequence and then a small number of luminance blocks used for data embedding are randomly selected in each macroblock based on another chaotic sequence. The usefulness of multilevel chaotic keys and privacy of the number of 4?×?4 luminance blocks enhance the security. The hidden information can be extracted directly from the encoded stream without resorting to the original video, and merely requires decoding the intra-prediction mode from bit stream rather than decoding the whole video. Experimental results show that the proposed hiding scheme can effectively embed information with little bit rate increase and almost no quality degradation.     

基于区间树硬件加速索引的Marching Cubes算法

为了充分利用GPU的海量线程并行架构,提高等值面可视化效率,提出一种基于区间树硬件加速索引的Marching Cubes算法.该算法在预计算阶段利用GPU构造多区域的区间树作为体数据体素的值域索引;在实时运行阶段根据用户给定的阈值,通过该索引并行地搜索活跃体素,并生成活跃体素的多级索引,然后分配线程处理活跃体素,抽取并绘制等值面.将文中算法应用到不同体数据上的实验结果表明,其能够显著地提高现有Marching Cubes算法的效率;与现有的GPU基准算法相比,最高能达到4～10倍的加速比.     

虚拟肝脏的规则和非规则手术切除技术

为了提高肝癌手术治疗计划的可靠性,在利用腹部CT图像数据进行肝脏三维重建的基础上,实现了任意角度对虚拟肝脏进行平面切割和切割面结构的显示;通过构造可以调节大小、位置的球体模型,实现了球体切除;通过在肝脏三维模型表面上勾画不规则封闭区域,实现了任意曲面肝脏切除;并依据肝内血管结构进行肝段划分,实现了解剖性肝段切除.临床实验结果表明,文中所述的技术能够满足虚拟手术的需求,有利于医生制定安全可靠的术前计划,提高手术成功率.     

连续体结构的参数化水平集统一优化

针对传统分步式结构优化设计的不足,提出一种同时进行结构拓扑、形状和尺寸统一优化的设计方法.首先采用水平集函数描述统一的结构优化模型和几何尺寸边界,通过引入紧支径向插值基函数将结构拓扑优化变量、形状优化变量和尺寸优化变量变换为基函数的扩展系数;然后取该扩展系数为设计变量,借助一种参数的变化表达3种优化要素对结构性能的影响,将复杂的多变量优化问题变换为相对简单的参数优化问题,有利于与相对成熟的优化算法相结合提高求解效率;进一步用R函数将其融合为一个整体,构造出统一优化模型,并用最优化准则法进行求解.最后通过数值案例证明了该方法的有效性和精确性.     

多站虚拟量测变换均值无源定位算法

在多站无源均值定位算法中,为了解决部分传感器间夹角过大或过小所导致的定位精度下降问题,提出一种基于虚拟量测变换的多传感器管理无源定位算法.首先在全局坐标系下分析了传感器间夹角对误差几何稀释度(GDOP)的影响,进而得到双站获得较好定位精度的夹角约束关系;其次针对不满足该约束关系的传感器组合提出一种虚拟量测变换定位算法,通过空间管理的方法达到对传感器的优化布站,并结合算法的实施步骤对其原理及特点进行了理论分析,尤其对变换前后的交点精度进行了比较.仿真结果表明虚拟量测算法的定位精度要明显优于均值算法,进而说明该算法的有效性及传感器管理在多站无源定位中的重要作用.     

一种调整簇阀值的加速聚类分析算法及其应用

针对航运信息中大样本聚类问题,根据k-means聚类过程中大部分簇的调整发生在初始迭代阶段的特性,提出了一种调整簇阀值的加速聚类方法,并对该算法进行实例测试,实验结果证明了该方法在满足原有的聚类精度的基础上,减少了聚类的计算量。本文将该方法应用到船舶航线设计中。     

基于Java点对点通信技术的DES密钥交换

介绍了使用Java的点对点通信技术,基于Diffie-Hellman规则,给出了IBM DES密钥交换的总体方案、算法和应用程序,详细说明了其中涉及的主要技术和方法,同时给出了在PC机上用二进制指数分解法实现大数模运算的算法分析和实现方案。