938 resultados para reconfigurable logic


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This study examined performance on transitive inference problems in children with developmental dyscalculia (DD), typically developing controls matched on IQ, working memory and reading skills, and in children with outstanding mathematical abilities. Whereas mainstream approaches currently consider DD as a domain-specific deficit, we hypothesized that the development of mathematical skills is closely related to the development of logical abilities, a domain-general skill. In particular, we expected a close link between mathematical skills and the ability to reason independently of one's beliefs. Our results showed that this was indeed the case, with children with DD performing more poorly than controls, and high maths ability children showing outstanding skills in logical reasoning about belief-laden problems. Nevertheless, all groups performed poorly on structurally equivalent problems with belief-neutral content. This is in line with suggestions that abstract reasoning skills (i.e. the ability to reason about content without real-life referents) develops later than the ability to reason about belief-inconsistent fantasy content.A video abstract of this article can be viewed at http://www.youtube.com/watch?v=90DWY3O4xx8.

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A reconfigurable reflectarray which exploits the dielectric anisotropy of liquid crystals (LC) has been designed to operate in the frequency range from 96 to 104 GHz. The unit cells are composed of three unequal length parallel dipoles placed above an LC substrate. The reflectarray has been designed using an accurate model which includes the effects of anisotropy and inhomogeneity. An effective permittivity that accounts for the real effects of the LC has also been used to simplify the analysis and design of the unit cells. The geometrical parameters of the cells have been adjusted to simultaneously improve the bandwidth, maximize the tunable phase-range and reduce the sensitivity to the angle of incidence. The performance of the LC based unit cells has been experimentally evaluated by measuring the reflection amplitude and phase of a reflectarray consisting of 52x54 identical cells. The good agreement between measurements and simulations validate the analysis and design techniques and demonstrate the capabilities of the proposed reflectarray to provide beam scanning in F band.

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Belief merging is an important but difficult problem in Artificial Intelligence, especially when sources of information are pervaded with uncertainty. Many merging operators have been proposed to deal with this problem in possibilistic logic, a weighted logic which is powerful for handling inconsistency and deal-ing with uncertainty. They often result in a possibilistic knowledge base which is a set of weighted formulas. Although possibilistic logic is inconsistency tolerant, it suffers from the well-known "drowning effect". Therefore, we may still want to obtain a consistent possibilistic knowledge base as the result of merging. In such a case, we argue that it is not always necessary to keep weighted information after merging. In this paper, we define a merging operator that maps a set of possibilistic knowledge bases and a formula representing the integrity constraints to a classical knowledge base by using lexicographic ordering. We show that it satisfies nine postulates that generalize basic postulates for propositional merging given in [11]. These postulates capture the principle of minimal change in some sense. We then provide an algorithm for generating the resulting knowledge base of our merging operator. Finally, we discuss the compatibility of our merging operator with propositional merging and establish the advantage of our merging operator over existing semantic merging operators in the propositional case.

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Several logic gates and switches can be accessed from two different combinations of a single set of fluorophore, receptor and spacer components.

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We consider the problem of self-healing in networks that are reconfigurable in the sense that they can change their topology during an attack. Our goal is to maintain connectivity in these networks, even in the presence of repeated adversarial node deletion, by carefully adding edges after each attack. We present a new algorithm, DASH, that provably ensures that: 1) the network stays connected even if an adversary deletes up to all nodes in the network; and 2) no node ever increases its degree by more than 2 log n, where n is the number of nodes initially in the network. DASH is fully distributed; adds new edges only among neighbors of deleted nodes; and has average latency and bandwidth costs that are at most logarithmic in n. DASH has these properties irrespective of the topology of the initial network, and is thus orthogonal and complementary to traditional topology- based approaches to defending against attack. We also prove lower-bounds showing that DASH is asymptotically optimal in terms of minimizing maximum degree increase over multiple attacks. Finally, we present empirical results on power-law graphs that show that DASH performs well in practice, and that it significantly outperforms naive algorithms in reducing maximum degree increase.

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An overview of research on reconfigurable architectures for network processing applications within the Institute of Electronics, Communications and Information Technology (ECIT) is presented. Three key network processing topics, namely node throughput, Quality of Service (QoS) and security are examined where custom reconfigurability allows network nodes to adapt to fluctuating network traffic and customer demands. Various architectural possibilities have been investigated in order to explore the options and tradeoffs available when using reconfigurability for packet/frame processing, packet-scheduling and data encryption/decryption. This research has shown there is no common approach that can be applied. Rather the methodologies used and the cost-benefits for incorporation of reconfigurability depend on each of the functions considered, for example being well suited to encryption/decryption but not packet/frame processing. © 2005 IEEE.

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Structural and functional information encoded in DNA combined with unique properties of nanomaterials could be of use for the construction of novel biocomputational circuits and intelligent biomedical nanodevices. However, at present their practical applications are still limited by either low reproducibility of fabrication, modest sensitivity, or complicated handling procedures. Here, we demonstrate the construction of label-free and switchable molecular logic gates that use specific conformation modulation of a guanine- and thymine- rich DNA, while the optical readout is enabled by the tunable alphabetical metamaterials, which serve as a substrate for surface enhanced Raman spectroscopy (MetaSERS). By computational and experimental investigations, we present a comprehensive solution to tailor the plasmonic responses of MetaSERS with respect to the metamaterial geometry, excitation energy, and polarization. Our tunable MetaSERS-based DNA logic is simple to operate, highly reproducible, and can be stimulated by ultra-low concentration of the external inputs, enabling an extremely sensitive detection of mercury ions.

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Reconfigurable bistate metasurfaces composed of interwoven spiral arrays with embedded pin diodes are proposed for single and dual polarisation operation. The switching capability is enabled by pin diodes that change the array response between transmission and reflection modes at the specified frequencies. The spiral conductors forming the metasurface also supply the dc bias for controlling pin diodes, thus avoiding the need of additional bias circuitry that can cause parasitic interference and affect the metasurface response. The simulation results show that proposed active metasurfaces exhibit good isolation between transmission and reflection states, while retaining excellent angular and polarisation stability with the large fractional bandwidth (FBW) inherent to the original passive arrays. © 2014 A. Vallecchi et al.

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We investigate periodic optomechanical arrays as reconfigurable platforms for engineering the coupling between multiple mechanical and electromagnetic modes and for exploring many-body phonon dynamics. Exploiting structural resonances in the coupling between light fields and collective motional modes of the array, we show that tunable effective long-range interactions between mechanical modes can be achieved. This paves the way towards the implementation of controlled phononic walks and heat transfer on densely connected graphs as well as the coherent transfer of excitations between distant elements of optomechanical arrays.

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Currently there is extensive theoretical work on inconsistencies in logic-based systems. Recently, algorithms for identifying inconsistent clauses in a single conjunctive formula have demonstrated that practical application of this work is possible. However, these algorithms have not been extended for full knowledge base systems and have not been applied to real-world knowledge. To address these issues, we propose a new algorithm for finding the inconsistencies in a knowledge base using existing algorithms for finding inconsistent clauses in a formula. An implementation of this algorithm is then presented as an automated tool for finding inconsistencies in a knowledge base and measuring the inconsistency of formulae. Finally, we look at a case study of a network security rule set for exploit detection (QRadar) and suggest how these automated tools can be applied.