915 research outputs found
Controlled Experimentation in Naturalistic Mobile Settings
Performing controlled user experiments on small devices in naturalistic
mobile settings has always proved to be a difficult undertaking for many Human
Factors researchers. Difficulties exist, not least, because mimicking natural
small device usage suffers from a lack of unobtrusive data to guide
experimental design, and then validate that the experiment is proceeding
naturally.Here we use observational data to derive a set of protocols and a
simple checklist of validations which can be built into the design of any
controlled experiment focused on the user interface of a small device. These,
have been used within a series of experimental designs to measure the utility
and application of experimental software. The key-point is the validation
checks -- based on the observed behaviour of 400 mobile users -- to ratify that
a controlled experiment is being perceived as natural by the user. While the
design of the experimental route which the user follows is a major factor in
the experimental setup, without check validations based on unobtrusive observed
data there can be no certainty that an experiment designed to be natural is
actually progressing as the design implies.Comment: 12 pages, 3 table
Random Feature-based Online Multi-kernel Learning in Environments with Unknown Dynamics
Kernel-based methods exhibit well-documented performance in various nonlinear
learning tasks. Most of them rely on a preselected kernel, whose prudent choice
presumes task-specific prior information. Especially when the latter is not
available, multi-kernel learning has gained popularity thanks to its
flexibility in choosing kernels from a prescribed kernel dictionary. Leveraging
the random feature approximation and its recent orthogonality-promoting
variant, the present contribution develops a scalable multi-kernel learning
scheme (termed Raker) to obtain the sought nonlinear learning function `on the
fly,' first for static environments. To further boost performance in dynamic
environments, an adaptive multi-kernel learning scheme (termed AdaRaker) is
developed. AdaRaker accounts not only for data-driven learning of kernel
combination, but also for the unknown dynamics. Performance is analyzed in
terms of both static and dynamic regrets. AdaRaker is uniquely capable of
tracking nonlinear learning functions in environments with unknown dynamics,
and with with analytic performance guarantees. Tests with synthetic and real
datasets are carried out to showcase the effectiveness of the novel algorithms.Comment: 36 page
Radiation Response of Oxide Dispersion Strengthened Alloy
Ferritic-martensitic (F/M) steels are known to have greater resistance to void swelling, higher thermal conductivities and lower thermal expansion coefficients than austenitic steels do. The strength and swelling resistance of F/M alloys can be further improved through adding fine dispersions of various yttria oxides. The majority of such oxide-dispersion-strengthened (ODS) alloys introduce dispersoids in ferrite phases. However, previous studies have shown that in the absence of dispersoids, the ferrite phase is significantly less swelling resistant than the tempered martensite phase.
A dual-phase 12Cr ODS alloy with improved corrosion and oxidation resistance exhibits promising microstructural stability and void swelling resistance under 3.5 MeV Fe^2+ ion irradiation at elevated temperatures. Dispersoids were originally present in both ferrite and tempered martensite grains, with the latter having a wider range of dispersoid sizes. In both phases dispersoids larger than 10 nm in diameter are incoherent with the matrix, while smaller dispersoids exhibit coherency. Beyond radiation damage of 60 displacements per atom (dpa), dispersoids in both phases appear to approach a near-identical equilibrium size, which depends on irradiation temperature. The evolution of dispersoids under irradiation was found to be related to the interface configuration. Grain morphology was found to be stable under irradiation up to a peak dpa of 800. Compared to other ferritic-martensitic alloys, the ion-induced swelling of this alloy is quite low, arising from swelling resistance associated with both tempered martensite and dispersoids in both phases. The swelling in tempered martensite is an order of magnitude less than in the ferrite phase
Energy-Efficient Transmission Schedule for Delay-Limited Bursty Data Arrivals under Non-Ideal Circuit Power Consumption
This paper develops a novel approach to obtaining energy-efficient
transmission schedules for delay-limited bursty data arrivals under non-ideal
circuit power consumption. Assuming a-prior knowledge of packet arrivals,
deadlines and channel realizations, we show that the problem can be formulated
as a convex program. For both time-invariant and time-varying fading channels,
it is revealed that the optimal transmission between any two consecutive
channel or data state changing instants, termed epoch, can only take one of the
three strategies: (i) no transmission, (ii) transmission with an
energy-efficiency (EE) maximizing rate over part of the epoch, or (iii)
transmission with a rate greater than the EE-maximizing rate over the whole
epoch. Based on this specific structure, efficient algorithms are then
developed to find the optimal policies that minimize the total energy
consumption with a low computational complexity. The proposed approach can
provide the optimal benchmarks for practical schemes designed for transmissions
of delay-limited data arrivals, and can be employed to develop efficient online
scheduling schemes which require only causal knowledge of data arrivals and
deadline requirements.Comment: 30 pages, 7 figure
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