14,550 research outputs found
Computation-Aware Data Aggregation
Data aggregation is a fundamental primitive in distributed computing wherein a network computes a function of every nodes\u27 input. However, while compute time is non-negligible in modern systems, standard models of distributed computing do not take compute time into account. Rather, most distributed models of computation only explicitly consider communication time.
In this paper, we introduce a model of distributed computation that considers both computation and communication so as to give a theoretical treatment of data aggregation. We study both the structure of and how to compute the fastest data aggregation schedule in this model. As our first result, we give a polynomial-time algorithm that computes the optimal schedule when the input network is a complete graph. Moreover, since one may want to aggregate data over a pre-existing network, we also study data aggregation scheduling on arbitrary graphs. We demonstrate that this problem on arbitrary graphs is hard to approximate within a multiplicative 1.5 factor. Finally, we give an O(log n ? log(OPT/t_m))-approximation algorithm for this problem on arbitrary graphs, where n is the number of nodes and OPT is the length of the optimal schedule
Convolutional neural networks: a magic bullet for gravitational-wave detection?
In the last few years, machine learning techniques, in particular
convolutional neural networks, have been investigated as a method to replace or
complement traditional matched filtering techniques that are used to detect the
gravitational-wave signature of merging black holes. However, to date, these
methods have not yet been successfully applied to the analysis of long
stretches of data recorded by the Advanced LIGO and Virgo gravitational-wave
observatories. In this work, we critically examine the use of convolutional
neural networks as a tool to search for merging black holes. We identify the
strengths and limitations of this approach, highlight some common pitfalls in
translating between machine learning and gravitational-wave astronomy, and
discuss the interdisciplinary challenges. In particular, we explain in detail
why convolutional neural networks alone cannot be used to claim a statistically
significant gravitational-wave detection. However, we demonstrate how they can
still be used to rapidly flag the times of potential signals in the data for a
more detailed follow-up. Our convolutional neural network architecture as well
as the proposed performance metrics are better suited for this task than a
standard binary classifications scheme. A detailed evaluation of our approach
on Advanced LIGO data demonstrates the potential of such systems as trigger
generators. Finally, we sound a note of caution by constructing adversarial
examples, which showcase interesting "failure modes" of our model, where inputs
with no visible resemblance to real gravitational-wave signals are identified
as such by the network with high confidence.Comment: First two authors contributed equally; appeared at Phys. Rev.
Gambling Alone? A Study of Solitary and Social Gambling in America
In his acclaimed 2000 book Bowling Alone, Robert Putnam documents a disturbing social trend of the broadest kind. Putnam cites a wide variety of data that indicate that over the past fifty years, Americans have become increasingly socially disengaged. In developing this theme, Putnam specifically cites the increase in casino gambling (and especially machine gambling) as evidence in support of his argument. Building on the empirical and theoretical work of Putnam, this exploratory article examines the subphenomenon of gambling alone by exploring sample survey data on solitary and social gambling behavior among adults who reside in Las Vegas, Nevada. Specifically, to further understand these phenomena, a number of demographic, attitudinal, and behavioral variables are examined for their explanatory power in predicting solitary vs. social gambling behavior
Technical Efficiency Effects of Technological Change: Another Perspective on GM Crops
An important approach to reducing persistent technical inefficiency is through technical change. This paper considers the case of genetically modified crop production. A stochastic frontier approach is used to examine how a drastic change from non-GM to GM technology effects the position of the production frontier as well as the extent and nature of technical inefficiency. A one-step method is applied to consider firm-level effects on technical inefficiency. Using soybean production from the U.S. we find that GM technology improves productivity and reduces technical inefficiency though these effects vary across farm characteristics.technical efficiency, technical change, genetically-modified, soybean, Crop Production/Industries, Research and Development/Tech Change/Emerging Technologies, D24, O33,
Anomalies of the infrared-active phonons in underdoped YBCO as an evidence for the intra-bilayer Josephson effect
The spectra of the far-infrared c-axis conductivity of underdoped YBCO
crystals exhibit dramatic changes of some of the phonon peaks when going from
the normal to the superconducting state. We show that the most striking of
these anomalies can be naturally explained by changes of the local fields
acting on the ions arising from the onset of inter- and intra-bilayer Josephson
effects.Comment: Revtex, epsf, 6 pages, 3 figures encapsulated in tex
Search for rare leptonic B decays at the Tevatron
Results of a search for the Flavor-Changing Neutral Current decay using collision data at TeV
collected at Fermilab Tevatron collider by the CDF and D{\O}detectors are
presented. CDF reports upper limits on and
at the 95% C.L. using 171 pb. The D{\O}Collaboration used 240 pb
to set an even more stringent limit on the branching ratio for of at the 95% C.L.Comment: 5 pages, 2 figures, submitted to DPF 2004 conference proceedings, UC
Riverside, C
Erasure Correction for Noisy Radio Networks
The radio network model is a well-studied model of wireless, multi-hop networks. However, radio networks make the strong assumption that messages are delivered deterministically. The recently introduced noisy radio network model relaxes this assumption by dropping messages independently at random.
In this work we quantify the relative computational power of noisy radio networks and classic radio networks. In particular, given a non-adaptive protocol for a fixed radio network we show how to reliably simulate this protocol if noise is introduced with a multiplicative cost of poly(log Delta, log log n) rounds where n is the number nodes in the network and Delta is the max degree. Moreover, we demonstrate that, even if the simulated protocol is not non-adaptive, it can be simulated with a multiplicative O(Delta log ^2 Delta) cost in the number of rounds. Lastly, we argue that simulations with a multiplicative overhead of o(log Delta) are unlikely to exist by proving that an Omega(log Delta) multiplicative round overhead is necessary under certain natural assumptions
Structural Change in Transition: A Role for Organizational Legitimacy? Evidence from Czech Agriculture
Market liberalization in Central and Eastern Europe was targeted at establishing incentives that would improve economic performance. While substantial reorganization of enterprises is observed, firms can also be observed which devote resources towards establishing organizational legitimacy. Motivations for such behavior are considered and empirical evidence of its relationship with technical efficiency using a distance function approach is analyzed for the case of Czech agriculture. Contrary to the expectation that such behavior would be inefficient, we find that firms reap private economic gains from legitimacy efforts through improved access to agricultural land, investment subsidies and firm internal social capital. However, its effect on technical efficiency depends on whether such legitimacy efforts are valued by stakeholders or understood as a norm. Evidence of the trade-off between gains or sustainability from legitimacy and reorganization thus brings a new perspective to the understanding of structural changes in transition.organizational legitimacy, efficiency, structural change, transition, agriculture, Industrial Organization, D21, D23, D24,
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