770 resultados para Affective 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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Combining numerical techniques with ideas from symbolic computation and with methods incorporating knowledge of science and mathematics leads to a new category of intelligent computational tools for scientists and engineers. These tools autonomously prepare simulation experiments from high-level specifications of physical models. For computationally intensive experiments, they automatically design special-purpose numerical engines optimized to perform the necessary computations. They actively monitor numerical and physical experiments. They interpret experimental data and formulate numerical results in qualitative terms. They enable their human users to control computational experiments in terms of high-level behavioral descriptions.

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The future of the software industry is today being shaped in the courtroom. Most discussions of intellectual property to date, however, have been frames as debates about how the existing law --- promulgated long before the computer revolution --- should be applied to software. This memo is a transcript of a panel discussion on what forms of legal protection should apply to software to best serve both the industry and society in general. After addressing that question we can consider what laws would bring this about.

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We describe the key role played by partial evaluation in the Supercomputer Toolkit, a parallel computing system for scientific applications that effectively exploits the vast amount of parallelism exposed by partial evaluation. The Supercomputer Toolkit parallel processor and its associated partial evaluation-based compiler have been used extensively by scientists at M.I.T., and have made possible recent results in astrophysics showing that the motion of the planets in our solar system is chaotically unstable.

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We present techniques for computing upper and lower bounds on the likelihoods of partial instantiations of variables in sigmoid and noisy-OR networks. The bounds determine confidence intervals for the desired likelihoods and become useful when the size of the network (or clique size) precludes exact computations. We illustrate the tightness of the obtained bounds by numerical experiments.

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Location is a primary cue in many context-aware computing systems, and is often represented as a global coordinate, room number, or Euclidean distance various landmarks. A user?s concept of location, however, is often defined in terms of regions in which common activities occur. We show how to partition a space into such regions based on patterns of observed user location and motion. These regions, which we call activity zones, represent regions of similar user activity, and can be used to trigger application actions, retrieve information based on previous context, and present information to users. We suggest that context-aware applications can benefit from a location representation learned from observing users. We describe an implementation of our system and present two example applications whose behavior is controlled by users? entry, exit, and presence in the zones.

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The dream of pervasive computing is slowly becoming a reality. A number of projects around the world are constantly contributing ideas and solutions that are bound to change the way we interact with our environments and with one another. An essential component of the future is a software infrastructure that is capable of supporting interactions on scales ranging from a single physical space to intercontinental collaborations. Such infrastructure must help applications adapt to very diverse environments and must protect people's privacy and respect their personal preferences. In this paper we indicate a number of limitations present in the software infrastructures proposed so far (including our previous work). We then describe the framework for building an infrastructure that satisfies the abovementioned criteria. This framework hinges on the concepts of delegation, arbitration and high-level service discovery. Components of our own implementation of such an infrastructure are presented.