基于可视化的C语言运行平台的设计

可视化技术给人机界面的开发带来了巨大的变化,程序语言编写及运行的可视化环境使人机界面的实现可以通过可视动画的交互方式进行。文章针对于C语言,采用VC＋＋工具进行可视化编辑环境的设计,实现C语言可视动画化运行及交互方式化运行的全过程。     

无线传感器网络定位理论和算法

定位技术作为网络协议和应用的基础,已经成为无线传感器网络重要的支撑技术,是传感器网络研究的核心问题之一.系统地总结了近年来定位理论和算法的最新研究进展.全面阐述了定位问题的形式化定义、定位问题复杂度分析、基于刚性理论的定位理论和定位问题可计算性研究的最新成果.通过对定位理论的研究可以更好地揭示定位技术的本质,回答很多定位技术相关的基本问题.此外,还深入分析了近年来典型的定位算法,介绍每种算法的设计思想,分析其适用范围和不足.最后给出定位理论和定位算法未来的研究方向.     

降低协同设计虚拟机启动开销的译码后指令缓存技术

协同设计虚拟机采用动态二进制翻译实现不同体系结构间的二进制兼容,对源指令的翻译和处理影响了协同设计虚拟机的启动性能.研究发现,在一个采用解释执行和翻译相结合的协同设计虚拟机中,处理非热点代码的解释执行是虚拟机启动开销的主要来源.发现了协同设计虚拟机中的解释例程局部性,并提出了一种硬件译码后指令缓存结构DICache(d...     

眼部疲劳状态检测算法的研究与实现

眼部状态的检测被认为是目前最准确可靠的疲劳驾驶状态识别方法,快速、准确地定位眼部是疲劳检测的关键.针对AdaBoost算法的训练过程中的样本权重过拟合问题进行了改进,提出了新的权重更新方法,即每一轮设定一个权重更新的阈值,避免了样本权重过拟合现象的出现.并针对影响检测速度的要素,结合肤色模型,缩小了搜索范围,减小了检测的错误接受率,并提高了检测速度.在Linux系统下采用QT编程实现了眼部疲劳检测的整个过程.实验结果验证了该算法定位和检测的准确性、实时性.     

基于OpenGVS半潜船操作模拟器视景系统的研究

为了满足半潜船作业人员学习和培训的需要,有必要在航海模拟器大环境下研发半潜船操作模拟器仿真系统。以船舶静力学为基础,实现了半潜船装载重大件货物的过程的动态稳性计算,以Visual C++6.0和OpenGVS场景管理软件为开发平台,研制开发了半潜船操作模拟器应具备的视景系统。该仿真系统实现了视点的转移和跟踪,通过设置在半潜船的驾驶台、甲板及外部三个虚拟相机,实时动态显示半潜船各种运动的状态,同时实现了半潜船操作模拟器几个模块间的相互通信,取得了很好的效果。     

一个通用的并行函数库

并行程序的设计在思路和方法上与串行程序有着本质的差别,其开发难度也比较大。为此,设计开发了一个通用的函数库来降低并行程序的开发难度。该函数库以MPI为基础,对并行程序开发中的常用功能进行了封装,具有一定的通用性。该函数库可以大大简化MPI并行程序的开发。并从区域分解、数组下标和循环变量的转换、数据交换和全局规约、输入输出等几个方面对该函数库进行了介绍,然后以数值求解二维拉普拉斯方程为例介绍了使用该函数库将串行程序改为并行程序的方法和步骤。目前已经成功地将其应用到风暴潮数值模式的并行化中,取得了较好的效果。     

On fuzzy renewal processes for fuzzy random variables and extended theorems

In this paper, we construct fuzzy renewal processes involving fuzzy random variables. We first extend the renewal processes to the fuzzy renewal processes where interarrival times, rewards, and stopping times are all fuzzy random variables. According to these fuzzy renewal processes, we then extend some theorems of renewal processes to those in fuzzy renewal processes. These are elementary renewal theorem, asymptotic expected average reward, and Wald's equation. In each part, we also give examples for applications. © 2010 Wiley Periodicals, Inc.     

Relaxation method for unsteady convection–diffusion equations

We propose and implement a relaxation method for solving unsteady linear and nonlinear convection–diffusion equations with continuous or discontinuity-like initial conditions. The method transforms a convection–diffusion equation into a relaxation system, which contains a stiff source term. The resulting relaxation system is then solved by a third-order accurate implicit–explicit (IMEX) Runge–Kutta method in time and a fifth-order finite difference WENO scheme in space. Numerical results show that the method can be used to effectively solve convection–diffusion equations with both smooth structures and discontinuities.     

Gaussian kernel optimization: Complex problem and a simple solution

The Gaussian kernel function implicitly defines the feature space of an algorithm and plays an essential role in the application of kernel methods. The parameter of Gaussian kernel function is a scalar that has significant influences on final results. However, until now, it is still unclear how to choose an optimal kernel parameter. In this paper, we propose a novel data-driven method to optimize the Gaussian kernel parameter, which only depends on the original dataset distribution and yields a simple solution to this complex problem. The proposed method is task irrelevant and can be used in any Gaussian kernel-based approach, including supervised and unsupervised machine learning. Simulation experiments demonstrate the efficacy of the obtained results. A user-friendly online calculator is implemented at: www.csbio.sjtu.edu.cn/bioinf/kernel/ for public use.     

Personalized video similarity measure

As an effective technique to manage and explore large scale of video collections, personalized video search has received great attentions in recent years. One of the key problems in the related technique development is how to design and evaluate the similarity measures. Most of the existing approaches simply adopt traditional Euclidean distance or its variants. Consequently, they generally suffer from two main disadvantages: (1) low effectiveness—retrieval accuracy is poor. One of main reasons is that very little research has been carried out on designing an effective fusion scheme for integrating multimodal information (e.g., text, audio and visual) from video sequences and (2) poor scalability—development process of the video similarity metrics is largely disconnected from that of the relevant database access methods (indexing structures). This article reports a new distance metric called personalized video distance to effectively fuse information about individual preference and multimodal properties into a compact signature. Moreover, a novel hashing-based indexing structure has been designed to facilitate fast retrieval process and better scalability. A set of comprehensive empirical studies have been carried out based on two large video test collections and carefully designed queries with different complexities. We observe significant improvements over the existing techniques on various aspects.