998 resultados para Could computing


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This paper describes a special-purpose neural computing system for face identification. The system architecture and hardware implementation are introduced in detail. An algorithm based on biomimetic pattern recognition has been embedded. For the total 1200 tests for face identification, the false rejection rate is 3.7% and the false acceptance rate is 0.7%.

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Quantum computing is a quickly growing research field. This article introduces the basic concepts of quantum computing, recent developments in quantum searching, and decoherence in a possible quantum dot realization.

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新的计算模式,普适计算和全局计算,正在作为高度分布式和移动计算的计算模式展现出来。这篇论文探讨了在抽象层面上支持这些新型计算模式的适合的形式化基础,关注在进程移动单位上的控制, 以便在分布式与移动计算环境下更好地协调进程的移动性。 论文的第一部分概述了针对分布式、移动计算的现有进程演算模型中的进程移动单元,并且设计了一种在此方面更优、更具弹性的进程框架。为了表示这种进程框架,我们提出了一种新的、针对移动和分布式系统的进程演算,这种进程演算的优点是动态、弹性的控制进程的移动单元;具体的思路就是扩展π- calculus以及其支持分布式和移动性的变体。我们把这种新的演算叫做Modular π-calculus。我们通过这种演算的提出来说明进程框架提供了一种针对移动进程更为合适的协调机制以及编程模型,例如移动的代理和动态组件载入的支持。之后,我们通过讨论互模拟的几种提法来具体说明能够反映演算设计的进程描述的关键,之后我们讨论了它们的具体性质。 本文的第二部分提出了一个对进程模型的行为和性质进行推理的规约框架。首先,提出了一个对Modularπ-calculus中进程的系统性质进行规约的模态逻辑。为了更好的理解该逻辑,文中对由这个逻辑推出的进程等价的特征进行了研究,并且证明了该逻辑的区分能力介于互模拟和结构一致之间。接下来关于这个规约框架的自动化,本文针对该逻辑和Modular π-calculus的有限控制子集,提出了模型检测算法,并且给出了算法正确性的证明。同时文中贯穿了一些实际且直观的例子,以展现本文提出的一组框架即演算、逻辑和模型算法的有效性。

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IEEE Comp Soc, IFIP, Tianjin Normal Univ

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A mathematical model on computation of molecular similarity was suggested, The algorithmic techniques for measuring the degree of similarity between pairs of three-dimensional chemical molecules was represented by modified interatomic distance matrices. Current work was carried out on Indigo 2 work station with Sybyl software. Four groups of molecules were used to compute the molecules similarity to testing the mathematical model with satisfactory results.

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The technology of seismic acquirement has been more and more intact in both land area and marine area, however, since the acquirement equipment can not handle the tasks in this both two kinds of prospects at the same time, it is very hard to acquire in the prospect of seashore area, and also the quality of the raw data is poor, the related work in seashore area has been a tough task. With the development of the level of exploration, acquired equipment and technology, a certain series of processing methods has been built up, which enhanced the resolving power, the ratio of signal to noise and the quality of imaging, these methods could meet most of the requirements of exploration and the development. What is more, more and more nowadays prospects are composed by two or more 3D sub-prospect, the differences between frequencies, energy levels and the ratios of signal to noise are definitely obvious, we can not perform finely construct analysis and interpretation of reservoir without solving these problems in matching different raw data. As for the prospect that composed by both seashore and marine ones, through the analysis on the characteristics on frequency, amplitude, polarity and multiples of land prospect and marine prospect, the methods on how to eliminate those differences mentioned above were researched, and this paper gives a series of methods includes the computing of matching factor, recognizing of time difference, recognizing of phase difference, matching frequency, collapsing of abnormal energy, frequency compensating and so on, to fulfill the attenuations of energy difference, frequency difference, time difference and phase difference, and what is more, improve the innovative methods: includes the quantities method to synthetically and automatically recognize time difference and phase difference on the basis of signal match technology and according to statistic rule. And distinct the differences on phase and frequency characteristics of received raw data between velocity seismometer and piezoelectricity seismometer, and deduces that there are 90 degrees gap between data from these two seismometers, thirdly, synthetically apply zone abnormal frequency processing, surface consistent abnormal frequency compensate, residual abnormal frequency compensate, stack time equilibrium and optimize the processing seis-flow, deal with the would-be problems, such as low signal and noise rate, low resolution, poor imaging and poor state of consistent. Gain excellent effect in Da-gang oil field.

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Numerical modeling of groundwater is very important for understanding groundwater flow and solving hydrogeological problem. Today, groundwater studies require massive model cells and high calculation accuracy, which are beyond single-CPU computer’s capabilities. With the development of high performance parallel computing technologies, application of parallel computing method on numerical modeling of groundwater flow becomes necessary and important. Using parallel computing can improve the ability to resolve various hydro-geological and environmental problems. In this study, parallel computing method on two main types of modern parallel computer architecture, shared memory parallel systems and distributed shared memory parallel systems, are discussed. OpenMP and MPI (PETSc) are both used to parallelize the most widely used groundwater simulator, MODFLOW. Two parallel solvers, P-PCG and P-MODFLOW, were developed for MODFLOW. The parallelized MODFLOW was used to simulate regional groundwater flow in Beishan, Gansu Province, which is a potential high-level radioactive waste geological disposal area in China. 1. The OpenMP programming paradigm was used to parallelize the PCG (preconditioned conjugate-gradient method) solver, which is one of the main solver for MODFLOW. The parallel PCG solver, P-PCG, is verified using an 8-processor computer. Both the impact of compilers and different model domain sizes were considered in the numerical experiments. The largest test model has 1000 columns, 1000 rows and 1000 layers. Based on the timing results, execution times using the P-PCG solver are typically about 1.40 to 5.31 times faster than those using the serial one. In addition, the simulation results are the exact same as the original PCG solver, because the majority of serial codes were not changed. It is worth noting that this parallelizing approach reduces cost in terms of software maintenance because only a single source PCG solver code needs to be maintained in the MODFLOW source tree. 2. P-MODFLOW, a domain decomposition–based model implemented in a parallel computing environment is developed, which allows efficient simulation of a regional-scale groundwater flow. The basic approach partitions a large model domain into any number of sub-domains. Parallel processors are used to solve the model equations within each sub-domain. The use of domain decomposition method to achieve the MODFLOW program distributed shared memory parallel computing system will process the application of MODFLOW be extended to the fleet of the most popular systems, so that a large-scale simulation could take full advantage of hundreds or even thousands parallel processors. P-MODFLOW has a good parallel performance, with the maximum speedup of 18.32 (14 processors). Super linear speedups have been achieved in the parallel tests, indicating the efficiency and scalability of the code. Parallel program design, load balancing and full use of the PETSc were considered to achieve a highly efficient parallel program. 3. The characterization of regional ground water flow system is very important for high-level radioactive waste geological disposal. The Beishan area, located in northwestern Gansu Province, China, is selected as a potential site for disposal repository. The area includes about 80000 km2 and has complicated hydrogeological conditions, which greatly increase the computational effort of regional ground water flow models. In order to reduce computing time, parallel computing scheme was applied to regional ground water flow modeling. Models with over 10 million cells were used to simulate how the faults and different recharge conditions impact regional ground water flow pattern. The results of this study provide regional ground water flow information for the site characterization of the potential high-level radioactive waste disposal.