“十二五”水利发展总体布局与建设主要任务——《全国水利发展“十二五”规划》解读之一

《全国水利发展“十二五”规划》在2011年中央1号文件指导下,对2011-2015年的水利改革发展做了全局研究和顶层设计.在分析水利建设面临的形势与挑战基础上,对“十二五”加快水利建设的总体思路与主要建设任务的确定进行了解读.     

实现分离多级存取结构的黑盒密钥共享体制

黑盒密钥共享体制和有限域上的密钥共享体制是不同的.该体制只要求主密钥空间是一个有限交换群,并且可以将群运算和随机挑选群元素等过程作为黑盒调用.尤其是,它与群的结构和除数无关.迄今为止,还没有造出有效的实现非门限存取结构的黑盒密钥共享体制.文中给出了任意交换群上的实现一类非门限存取结构的黑盒密钥共享体制的构造方法.作者使用的工具是环上单调张成方案.首先,作者提出弱单调张成方案的概念,并给出了使用弱单调张成方案构造单调张成方案的方法.然后,利用有理数域上的单调张成方案和有限域上的单调张成方案,构造出了一对互素的弱单调张成方案,最终构造出了实现一类非门限存取结构——分离多级存取结构的有效黑盒密钥共享体制.作者构造的新体制可用于构造新的实现分离多级存取结构的环上安全多方计算协议、线性整密钥共享体制、分布式RSA签名协议和新的零知识证明协议.     

PET瓶封盖质量在线检测系统的设计与实现

设计了一套完整的基于DSP+ARM双核处理器的PET瓶封盖质量检测系统。首先通过DSP DM642完成对图像传感器MT9P031的RAW原始数据采集,然后对采集的PET瓶图像进行定位并实现相关的图像处理算法,最后采用ARM11嵌入式系统对整个传动设备进行监控。经过实际生产线的应用证明,该在线检测系统能够胜任在高速PET瓶封盖生产线中的应用。     

基于 GPU 和 Kinect 的快速物体重建

便宜的物体快速三维建模技术是当前计算机视觉领域重要的研究课题.给出了一种基于Kinect传感器的快速物体重建方法,以及基于该方法的一种图形处理器 (Graphic processing unit, GPU)原型系统实现.本文方法主要分为两步: 1)系统的初始标定; 2)全自动的物体重建.对于系统初始标定,提出了一种简单易用的粗标定方法;对于物体重建,提出一种全自动的快速物体重建方法.本文方法鲁棒性高,在出现点云配准错误时仍然能够稳定地得到较理想的重建模型.针对环闭合(Loop-closure)问题,提出了一种全局的点云配准方法.对几类物体的重建实验结果表明,本文方法方便实用,且能得到较好的重建效果.此外,本文还探索了有遮挡物体的重建问题.将本文方法应用于有遮挡物体的重建,也取得了较好的重建效果.     

A Tabu search algorithm for the network pricing problem

In this paper, we propose an efficient Tabu Search procedure for solving the NP-hard network pricing problem. By exploiting the problem's features, the algorithm allows the near-optimal solution of problem instances that are out of reach of exact combinatorial methods.     

Solving knapsack problems on GPU

A parallel implementation via CUDA of the dynamic programming method for the knapsack problem on NVIDIA GPU is presented. A GTX 260 card with 192 cores (1.4 GHz) is used for computational tests and processing times obtained with the parallel code are compared to the sequential one on a CPU with an Intel Xeon 3.0 GHz. The results show a speedup factor of 26 for large size problems. Furthermore, in order to limit the communication between the CPU and the GPU, a compression technique is presented which decreases significantly the memory occupancy.     

GPGPU implementation of growing neural gas: Application to 3D scene reconstruction

Self-organising neural models have the ability to provide a good representation of the input space. In particular the Growing Neural Gas (GNG) is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation. However, this type of learning is time-consuming, especially for high-dimensional input data. Since real applications often work under time constraints, it is necessary to adapt the learning process in order to complete it in a predefined time. This paper proposes a Graphics Processing Unit (GPU) parallel implementation of the GNG with Compute Unified Device Architecture (CUDA). In contrast to existing algorithms, the proposed GPU implementation allows the acceleration of the learning process keeping a good quality of representation. Comparative experiments using iterative, parallel and hybrid implementations are carried out to demonstrate the effectiveness of CUDA implementation. The results show that GNG learning with the proposed implementation achieves a speed-up of 6×$6\times$ compared with the single-threaded CPU implementation. GPU implementation has also been applied to a real application with time constraints: acceleration of 3D scene reconstruction for egomotion, in order to validate the proposal.     

Parallel iteratively regularized Gauss–Newton method for systems of nonlinear ill-posed equations

We propose a parallel version of the iteratively regularized Gauss–Newton method for solving a system of ill-posed equations. Under certain widely used assumptions, the convergence rate of the parallel method is established. Numerical experiments show that the parallel iteratively regularized Gauss–Newton method is computationally convenient for dealing with underdetermined systems of nonlinear equations on parallel computers, especially when the number of unknowns is much larger than that of equations.     

Function simulation,graph grammars and colourings

We prove that to any partial function ? defined on a finite set, there corresponds an infinite class of graphs that could be generated by a graph grammar such that each graph in the class represents the function in the sense that evaluation of the function at any point x of its domain can be simulated by finding the unique extension of a partial vertex colouring of the graph specified by x. We show that in the proposed setup, generating such simulator graphs as well as finding the colouring extensions can be computed effectively in polynomial time. We also discuss some applications of this scenario in producing instances of the graph colouring problem near its phase transition that can be applied in a cryptographic setting.     

Updating method for the computation of orbits in parallel and sequential dynamical systems

In this article, we provide a matrix method in order to compute orbits of parallel and sequential dynamical systems on Boolean functions. In this sense, we develop algorithms for systems defined over directed (and undirected) graphs when the evolution operator is a general minterm or maxterm and, likewise, when it is constituted by independent local Boolean functions, so providing a new tool for the study of orbits of these dynamical systems.