1,784 research outputs found
Synthesis and Optimization of Reversible Circuits - A Survey
Reversible logic circuits have been historically motivated by theoretical
research in low-power electronics as well as practical improvement of
bit-manipulation transforms in cryptography and computer graphics. Recently,
reversible circuits have attracted interest as components of quantum
algorithms, as well as in photonic and nano-computing technologies where some
switching devices offer no signal gain. Research in generating reversible logic
distinguishes between circuit synthesis, post-synthesis optimization, and
technology mapping. In this survey, we review algorithmic paradigms ---
search-based, cycle-based, transformation-based, and BDD-based --- as well as
specific algorithms for reversible synthesis, both exact and heuristic. We
conclude the survey by outlining key open challenges in synthesis of reversible
and quantum logic, as well as most common misconceptions.Comment: 34 pages, 15 figures, 2 table
LCrowdV: Generating Labeled Videos for Simulation-based Crowd Behavior Learning
We present a novel procedural framework to generate an arbitrary number of
labeled crowd videos (LCrowdV). The resulting crowd video datasets are used to
design accurate algorithms or training models for crowded scene understanding.
Our overall approach is composed of two components: a procedural simulation
framework for generating crowd movements and behaviors, and a procedural
rendering framework to generate different videos or images. Each video or image
is automatically labeled based on the environment, number of pedestrians,
density, behavior, flow, lighting conditions, viewpoint, noise, etc.
Furthermore, we can increase the realism by combining synthetically-generated
behaviors with real-world background videos. We demonstrate the benefits of
LCrowdV over prior lableled crowd datasets by improving the accuracy of
pedestrian detection and crowd behavior classification algorithms. LCrowdV
would be released on the WWW
MMIC power amplifiers as local oscillator drivers for FIRST
The Heterodyne Instrument for the Far-Infrared and Sub- millimeter Telescope requires local oscillators well into the terahertz frequency range. The mechanism to realize the local oscillators will involve synthesizers, active multiplier chains (AMC's) with output frequencies from 71 - 112.5 GHz, power amplifiers to amplify the AMC signals, and chains of Schottky diode multipliers to achieve terahertz frequencies. We will present the latest state-of-the-art results on 70 - 115 GHz Monolithic Millimeter-wave Integrated Circuit power amplifier technology
Photonic Analogue of Two-dimensional Topological Insulators and Helical One-Way Edge Transport in Bi-Anisotropic Metamaterials
Recent progress in understanding the topological properties of condensed
matter has led to the discovery of time-reversal invariant topological
insulators. Because of limitations imposed by nature, topologically non-trivial
electronic order seems to be uncommon except in small-band-gap semiconductors
with strong spin-orbit interactions. In this Article we show that artificial
electromagnetic structures, known as metamaterials, provide an attractive
platform for designing photonic analogues of topological insulators. We
demonstrate that a judicious choice of the metamaterial parameters can create
photonic phases that support a pair of helical edge states, and that these edge
states enable one-way photonic transport that is robust against disorder.Comment: 13 pages, 3 figure
Complement C3 Inhibitor Pegcetacoplan for Geographic Atrophy Secondary to Age-Related Macular Degeneration : A Randomized Phase 2 Trial
Copyright © 2019 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.Peer reviewedPublisher PD
Traffic Instabilities in Self-Organized Pedestrian Crowds
In human crowds as well as in many animal societies, local interactions among
individuals often give rise to self-organized collective organizations that
offer functional benefits to the group. For instance, flows of pedestrians
moving in opposite directions spontaneously segregate into lanes of uniform
walking directions. This phenomenon is often referred to as a smart collective
pattern, as it increases the traffic efficiency with no need of external
control. However, the functional benefits of this emergent organization have
never been experimentally measured, and the underlying behavioral mechanisms
are poorly understood. In this work, we have studied this phenomenon under
controlled laboratory conditions. We found that the traffic segregation
exhibits structural instabilities characterized by the alternation of organized
and disorganized states, where the lifetime of well-organized clusters of
pedestrians follow a stretched exponential relaxation process. Further analysis
show that the inter-pedestrian variability of comfortable walking speeds is a
key variable at the origin of the observed traffic perturbations. We show that
the collective benefit of the emerging pattern is maximized when all
pedestrians walk at the average speed of the group. In practice, however, local
interactions between slow- and fast-walking pedestrians trigger global
breakdowns of organization, which reduce the collective and the individual
payoff provided by the traffic segregation. This work is a step ahead toward
the understanding of traffic self-organization in crowds, which turns out to be
modulated by complex behavioral mechanisms that do not always maximize the
group's benefits. The quantitative understanding of crowd behaviors opens the
way for designing bottom-up management strategies bound to promote the
emergence of efficient collective behaviors in crowds.Comment: Article published in PLoS Computational biology. Freely available
here:
http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.100244
Quantifying Inactive Lithium in Lithium Metal Batteries
Inactive lithium (Li) formation is the immediate cause of capacity loss and
catastrophic failure of Li metal batteries. However, the chemical component and
the atomic level structure of inactive Li have rarely been studied due to the
lack of effective diagnosis tools to accurately differentiate and quantify Li+
in solid electrolyte interphase (SEI) components and the electrically isolated
unreacted metallic Li0, which together comprise the inactive Li. Here, by
introducing a new analytical method, Titration Gas Chromatography (TGC), we can
accurately quantify the contribution from metallic Li0 to the total amount of
inactive Li. We uncover that the Li0, rather than the electrochemically formed
SEI, dominates the inactive Li and capacity loss. Using cryogenic electron
microscopies to further study the microstructure and nanostructure of inactive
Li, we find that the Li0 is surrounded by insulating SEI, losing the electronic
conductive pathway to the bulk electrode. Coupling the measurements of the Li0
global content to observations of its local atomic structure, we reveal the
formation mechanism of inactive Li in different types of electrolytes, and
identify the true underlying cause of low Coulombic efficiency in Li metal
deposition and stripping. We ultimately propose strategies to enable the highly
efficient Li deposition and stripping to enable Li metal anode for next
generation high energy batteries
日本経団連が国家エネルギー戦略確立を提言
This paper describes the outcomes of an ongoing collaboration between Siemens and the University of Oxford, with the goal of facilitating the design of ontologies and their deployment in applications. Ontologies are often used in industry to capture the conceptual information models underpinning applications. We start by describing the role that such models play in two use cases in the manufacturing and energy production sectors. Then, we discuss the formalisation of information models using ontologies, and the relevant reasoning services. Finally, we present SOMM—a tool that supports engineers with little background on semantic technologies in the creation of ontology-based models and in populating them with data. SOMM implements a fragment of OWL 2 RL extended with a form of integrity constraints for data validation, and it comes with support for schema and data reasoning, as well as for model integration. Our preliminary evaluation demonstrates the adequacy of SOMM’s functionality and performance
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