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

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

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

Founders\u27 Day 1958

Founders Day, 3/14/1958. Reel #3