460 research outputs found

    MatLab vs. Python vs. R

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    MatLab vs. Python vs. R

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    Epitaxial lateral overgrowth of a-plane GaN by metalorganic chemical vapor deposition

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    We report on epitaxial lateral overgrowth (ELO) of (112¯0) a-plane GaN by metalorganic chemical vapor deposition. Different growth rates of Ga- and N-polar wings together with wing tilt create a major obstacle for achieving a smooth, fully coalesced surface in ELOa-plane GaN. To address this issue a two-step growth method was employed to provide a large aspect ratio of height to width in the first growth step followed by enhanced lateral growth in the second by controlling the growth temperature. By this method, the average ratio of Ga- to N-polar wing growth rate has been reduced from 4–6 to 1.5–2, which consequently reduced the wing-tilt induced height difference between the two approaching wings at the coalescence front, thereby making their coalescence much easier. Transmission electron microscopy showed that the threading dislocation density in the wing regions was 1.0×108 cm−2, more than two orders of magnitude lower than that in the window regions (4.2×1010 cm−2). However, a relatively high density of basal stacking faults of 1.2×104 cm−1 was still present in the wing regions as compared to c -plane GaN, where they are rarely observed away from the substrate. Atomic force microscopy(AFM) measurements showed two orders of magnitude higher density of surface pits in the window than in the wing regions, which were considered to be terminated by dislocations (partial ones related to stacking faults and full ones) on the surface. The existence of basal stacking faults was also revealed by AFM measurements on the a-plane ELO sample after wet chemical etching in hot H3PO4∕H2SO4 (1:1). The extensions of Ga-polar wings near the meeting fronts were almost free of stacking faults. The improvement of crystalline quality in the overgrown layer by ELO was also verified by near field scanning optical microscopy and time-resolved photoluminescence measurements; the former showing strongly enhanced luminescence from the wing regions, and the latter indicating longer decay times (0.25 ns) compared to a standard a-plane GaN template (40 ps)

    Discovering Physical Interaction Vulnerabilities in IoT Deployments

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    Internet of Things (IoT) applications drive the behavior of IoT deployments according to installed sensors and actuators. It has recently been shown that IoT deployments are vulnerable to physical interactions, caused by design flaws or malicious intent, that can have severe physical consequences. Yet, extant approaches to securing IoT do not translate the app source code into its physical behavior to evaluate physical interactions. Thus, IoT consumers and markets do not possess the capability to assess the safety and security risks these interactions present. In this paper, we introduce the IoTSeer security service for IoT deployments, which uncovers undesired states caused by physical interactions. IoTSeer operates in four phases (1) translation of each actuation command and sensor event in an app source code into a hybrid I/O automaton that defines an app's physical behavior, (2) combining apps in a novel composite automaton that represents the joint physical behavior of interacting apps, (3) applying grid-based testing and falsification to validate whether an IoT deployment conforms to desired physical interaction policies, and (4) identification of the root cause of policy violations and proposing patches that guide users to prevent them. We use IoTSeer in an actual house with 13 actuators and six sensors with 37 apps and demonstrate its effectiveness and performance

    Split ring resonator-coupled enhanced transmission through a single subwavelength aperture

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    We report the enhanced transmission of electromagnetic waves through a single subwavelength aperture by making use of the resonance behavior of a split ring resonator (SRR) at microwave frequencies. By placing a single SRR at the near-field of the aperture, strongly localized electromagnetic fields are effectively coupled to the aperture with a radius that is twenty times smaller than the resonance wavelength. We obtained 740-fold transmission enhancement by exciting the electric resonance of SRR. A different coupling mechanism, through the magnetic resonance of SRR, is also verified to yield enhanced transmission. Good agreement is obtained between the microwave measurements and numerical simulations.Comment: 14 pages, 4 figures, to be submitted to PR

    Instance generation via generator instances

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    Funding: UK EPSRC grant EP/P015638/1.Access to good benchmark instances is always desirable when developing new algorithms, new constraint models, or when comparing existing ones. Hand-written instances are of limited utility and are time-consuming to produce. A common method for generating instances is constructing special purpose programs for each class of problems. This can be better than manually producing instances, but developing such instance generators also has drawbacks. In this paper, we present a method for generating graded instances completely automatically starting from a class-level problem specification. A graded instance in our present setting is one which is neither too easy nor too difficult for a given solver. We start from an abstract problem specification written in the Essence language and provide a system to transform the problem specification, via automated type-specific rewriting rules, into a new abstract specification which we call a generator specification. The generator specification is itself parameterised by a number of integer parameters; these are used to characterise a certain region of the parameter space. The solutions of each such generator instance form valid problem instances. We use the parameter tuner irace to explore the space of possible generator parameters, aiming to find parameter values that yield graded instances. We perform an empirical evaluation of our system for five problem classes from CSPlib, demonstrating promising results.Postprin
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