22,703 research outputs found
The Configurable SAT Solver Challenge (CSSC)
It is well known that different solution strategies work well for different
types of instances of hard combinatorial problems. As a consequence, most
solvers for the propositional satisfiability problem (SAT) expose parameters
that allow them to be customized to a particular family of instances. In the
international SAT competition series, these parameters are ignored: solvers are
run using a single default parameter setting (supplied by the authors) for all
benchmark instances in a given track. While this competition format rewards
solvers with robust default settings, it does not reflect the situation faced
by a practitioner who only cares about performance on one particular
application and can invest some time into tuning solver parameters for this
application. The new Configurable SAT Solver Competition (CSSC) compares
solvers in this latter setting, scoring each solver by the performance it
achieved after a fully automated configuration step. This article describes the
CSSC in more detail, and reports the results obtained in its two instantiations
so far, CSSC 2013 and 2014
PID control system analysis, design, and technology
Designing and tuning a proportional-integral-derivative
(PID) controller appears to be conceptually intuitive, but can
be hard in practice, if multiple (and often conflicting) objectives
such as short transient and high stability are to be achieved.
Usually, initial designs obtained by all means need to be adjusted
repeatedly through computer simulations until the closed-loop
system performs or compromises as desired. This stimulates
the development of "intelligent" tools that can assist engineers
to achieve the best overall PID control for the entire operating
envelope. This development has further led to the incorporation
of some advanced tuning algorithms into PID hardware modules.
Corresponding to these developments, this paper presents a
modern overview of functionalities and tuning methods in patents,
software packages and commercial hardware modules. It is seen
that many PID variants have been developed in order to improve
transient performance, but standardising and modularising PID
control are desired, although challenging. The inclusion of system
identification and "intelligent" techniques in software based PID
systems helps automate the entire design and tuning process to
a useful degree. This should also assist future development of
"plug-and-play" PID controllers that are widely applicable and
can be set up easily and operate optimally for enhanced productivity,
improved quality and reduced maintenance requirements
Synthetic Gene Circuits: Design with Directed Evolution
Synthetic circuits offer great promise for generating insights into nature's underlying design principles or forward engineering novel biotechnology applications. However, construction of these circuits is not straightforward. Synthetic circuits generally consist of components optimized to function in their natural context, not in the context of the synthetic circuit. Combining mathematical modeling with directed evolution offers one promising means for addressing this problem. Modeling identifies mutational targets and limits the evolutionary search space for directed evolution, which alters circuit performance without the need for detailed biophysical information. This review examines strategies for integrating modeling and directed evolution and discusses the utility and limitations of available methods
Analysis of a Waveguide-Fed Metasurface Antenna
The metasurface concept has emerged as an advantageous reconfigurable antenna
architecture for beam forming and wavefront shaping, with applications that
include satellite and terrestrial communications, radar, imaging, and wireless
power transfer. The metasurface antenna consists of an array of metamaterial
elements distributed over an electrically large structure, each subwavelength
in dimension and with subwavelength separation between elements. In the antenna
configuration we consider here, the metasurface is excited by the fields from
an attached waveguide. Each metamaterial element can be modeled as a
polarizable dipole that couples the waveguide mode to radiation modes. Distinct
from the phased array and electronically scanned antenna (ESA) architectures, a
dynamic metasurface antenna does not require active phase shifters and
amplifiers, but rather achieves reconfigurability by shifting the resonance
frequency of each individual metamaterial element. Here we derive the basic
properties of a one-dimensional waveguide-fed metasurface antenna in the
approximation that the metamaterial elements do not perturb the waveguide mode
and are non-interacting. We derive analytical approximations for the array
factors of the 1D antenna, including the effective polarizabilities needed for
amplitude-only, phase-only, and binary constraints. Using full-wave numerical
simulations, we confirm the analysis, modeling waveguides with slots or
complementary metamaterial elements patterned into one of the surfaces.Comment: Original manuscript as submitted to Physical Review Applied (2017).
14 pages, 14 figure
Reconfigurable Reflectarrays and Array Lenses for Dynamic Antenna Beam Control: A Review
Advances in reflectarrays and array lenses with electronic beam-forming
capabilities are enabling a host of new possibilities for these
high-performance, low-cost antenna architectures. This paper reviews enabling
technologies and topologies of reconfigurable reflectarray and array lens
designs, and surveys a range of experimental implementations and achievements
that have been made in this area in recent years. The paper describes the
fundamental design approaches employed in realizing reconfigurable designs, and
explores advanced capabilities of these nascent architectures, such as
multi-band operation, polarization manipulation, frequency agility, and
amplification. Finally, the paper concludes by discussing future challenges and
possibilities for these antennas.Comment: 16 pages, 12 figure
Semi-supervised Tuning from Temporal Coherence
Recent works demonstrated the usefulness of temporal coherence to regularize
supervised training or to learn invariant features with deep architectures. In
particular, enforcing smooth output changes while presenting temporally-closed
frames from video sequences, proved to be an effective strategy. In this paper
we prove the efficacy of temporal coherence for semi-supervised incremental
tuning. We show that a deep architecture, just mildly trained in a supervised
manner, can progressively improve its classification accuracy, if exposed to
video sequences of unlabeled data. The extent to which, in some cases, a
semi-supervised tuning allows to improve classification accuracy (approaching
the supervised one) is somewhat surprising. A number of control experiments
pointed out the fundamental role of temporal coherence.Comment: Under review as a conference paper at ICLR 201
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