4,857 research outputs found
Laboratory performances of the solar multichannel resonant scattering spectrometer prototype of the GOLF-New Generation instrument
This article quickly summarizes the performances and results of the GOLF/SoHO
resonant spectrometer, thus justifying to go a step further. We then recall the
characteristics of the multichannel resonant GOLF-NG spectrometer and present
the first successful performances of the laboratory tests on the prototype and
also the limitations of this first technological instrument. Scientific
questions and an observation strategy are discussed.Comment: 8 pages, 8 figures, published in Astronomical Note
The solar energetic balance revisited by young solar analogs, helioseismology and neutrinos
The energetic balance of the Standard Solar Model (SSM) results from an
equilibrium between nuclear energy production, energy transfer, and
photospheric emission. In this letter, we derive an order of magnitude of
several % for the loss of energy in kinetic energy, magnetic energy, and X or
UV radiation during the whole solar lifetime from the observations of the
present Sun. We also estimate the mass loss from the observations of young
solar analogs which could reach up to 30% of the current mass. We deduce new
models of the present Sun, their associated neutrino fluxes, and their internal
sound-speed profile. This approach sheds quantitative lights on the
disagreement between the sound speed obtained by helioseismology and the sound
speed derived from the SSM including the updated photospheric CNO abundances,
based on recent observations. We conclude that about 20% of the present
discrepancy could come from the incorrect description of the early phases of
the Sun, its activity, its initial mass and mass-loss history. This study has
obvious consequences on the solar system formation and the early evolution of
the closest planets.Comment: 14 pages, 3 figures; Published in ApJ lett 201
Concluding remarks on Solar and Stellar Activities and related planets
The symposium has shown the dynamism of this rapidly evolving discipline. I
shall concentrate here on some highlights and some complementary informations.
I conclude on open questions with some perspectives on solar & stellar activity
and related planets.Comment: 17 pages, 13 figures, concluding remarks of IAU264 in RIO, 200
Federated and autonomic management of multimedia services
Over the years, the Internet has significantly evolved in size and complexity. Additionally, the modern multimedia services it offers have considerably more stringent Quality of Service (QoS) requirements than traditional static services. These factors contribute to the ever-increasing complexity and cost to manage the Internet and its services. In the dissertation, a novel network management architecture is proposed to overcome these problems. It supports QoS-guarantees of multimedia services across the Internet, by setting up end-to-end network federations. A network federation is defined as a persistent cross-organizational agreement that enables the cooperating networks to share capabilities. Additionally, the architecture incorporates aspects from autonomic network management to tackle the ever-growing management complexity of modern communications networks. Specifically, a hierarchical approach is presented, which guarantees scalable collaboration of huge amounts of self-governing autonomic management components
Solar neutrinos, helioseismology and the solar internal dynamics
Neutrinos are fundamental particles ubiquitous in the Universe. Their
properties remain elusive despite more than 50 years of intense research
activity. In this review we remind the reader of the noticeable properties of
these particles and of the stakes of the solar neutrino puzzle. The Standard
Solar Model triggered persistent efforts in fundamental Physics to predict the
solar neutrino fluxes, and its constantly evolving predictions have been
regularly compared to the detected neutrino signals. Anticipating that this
standard model could not reproduce the internal solar dynamics, a SEismic Solar
Model was developed which enriched theoretical neutrino flux predictions with
in situ observation of acoustic waves propagating in the Sun. This review
reminds the historical steps, from the pioneering Homestake detection, the
GALLEX- SAGE captures of the first pp neutrinos and emphasizes the importance
of the Superkamiokande and SNO detectors to demonstrate that the solar-emitted
electronic neutrinos are partially transformed into other neutrino flavors
before reaching the Earth. The success of BOREXINO in detecting the 7 Be
neutrino signal justifies the building of a new generation of detectors to
measure the entire solar neutrino spectrum. A coherent picture emerged from
neutrino physics and helioseismology. Today, new paradigms take shape:
determining the masses of neutrinos and the research on the Sun is focusing on
the dynamical aspects and on signature of dark matter. The third part of the
review is dedicated to this prospect. The understanding of the crucial role of
both rotation and magnetism in solar physics benefit from SoHO, SDO, and PICARD
space observations. For now, the particle and stellar challenges seem
decoupled, but this is only a superficial appearance. The development of
asteroseismology shows the far-reaching impact of Neutrino and Stellar
Astronomy.Comment: 60 pages, 12 figures Invited review in press in Report on Progress in
Physic
Integrated Inference and Learning of Neural Factors in Structural Support Vector Machines
Tackling pattern recognition problems in areas such as computer vision,
bioinformatics, speech or text recognition is often done best by taking into
account task-specific statistical relations between output variables. In
structured prediction, this internal structure is used to predict multiple
outputs simultaneously, leading to more accurate and coherent predictions.
Structural support vector machines (SSVMs) are nonprobabilistic models that
optimize a joint input-output function through margin-based learning. Because
SSVMs generally disregard the interplay between unary and interaction factors
during the training phase, final parameters are suboptimal. Moreover, its
factors are often restricted to linear combinations of input features, limiting
its generalization power. To improve prediction accuracy, this paper proposes:
(i) Joint inference and learning by integration of back-propagation and
loss-augmented inference in SSVM subgradient descent; (ii) Extending SSVM
factors to neural networks that form highly nonlinear functions of input
features. Image segmentation benchmark results demonstrate improvements over
conventional SSVM training methods in terms of accuracy, highlighting the
feasibility of end-to-end SSVM training with neural factors
Joint in-network video rate adaptation and measurement-based admission control: algorithm design and evaluation
The important new revenue opportunities that multimedia services offer to network and service providers come with important management challenges. For providers, it is important to control the video quality that is offered and perceived by the user, typically known as the quality of experience (QoE). Both admission control and scalable video coding techniques can control the QoE by blocking connections or adapting the video rate but influence each other's performance. In this article, we propose an in-network video rate adaptation mechanism that enables a provider to define a policy on how the video rate adaptation should be performed to maximize the provider's objective (e.g., a maximization of revenue or QoE). We discuss the need for a close interaction of the video rate adaptation algorithm with a measurement based admission control system, allowing to effectively orchestrate both algorithms and timely switch from video rate adaptation to the blocking of connections. We propose two different rate adaptation decision algorithms that calculate which videos need to be adapted: an optimal one in terms of the provider's policy and a heuristic based on the utility of each connection. Through an extensive performance evaluation, we show the impact of both algorithms on the rate adaptation, network utilisation and the stability of the video rate adaptation. We show that both algorithms outperform other configurations with at least 10 %. Moreover, we show that the proposed heuristic is about 500 times faster than the optimal algorithm and experiences only a performance drop of approximately 2 %, given the investigated video delivery scenario
Large deviations of an infinite-server system with a linearly scaled background process
This paper studies an infinite-server queue in a Markov environment, that is, an infinite-server queue with arrival rates and service times depending on the state of a Markovian background process. We focus on the probability that the number of jobs in the system attains an unusually high value. Scaling the arrival rates ¿i¿i by a factor NN and the transition rates ¿ij¿ij of the background process as well, a large-deviations based approach is used to examine such tail probabilities (where NN tends to 88). The paper also presents qualitative properties of the system’s behavior conditional on the rare event under consideration happening. Keywords: Queues; Infinite-server systems; Markov modulation; Large deviation
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