1,126 research outputs found
Towards an automatic system for monitoring of CN2 and wind speed profiles with GeMS
Wide Field Adaptive Optics (WFAO) systems represent the more sophisticated AO
systems available today at large telescopes. A critical aspect for these WFAO
systems in order to deliver an optimised performance is the knowledge of the
vertical spatiotemporal distribution of the CN2 and the wind speed. Previous
studies (Cortes et al., 2012) already proved the ability of GeMS (the Gemini
Multi-Conjugated AO system) in retrieving CN2 and wind vertical stratification
using the telemetry data. To assess the reliability of the GeMS wind speed
estimates a preliminary study (Neichel et al., 2014) compared wind speed
retrieved from GeMS with that obtained with the atmospherical model Meso-Nh on
a small sample of nights providing promising results. The latter technique is
very reliable for the wind speed vertical stratification. The model outputs
gave, indeed, an excellent agreement with a large sample of radiosoundings (~
50) both in statistical terms and on individual flights (Masciadri et al.,
2013). Such a tool can therefore be used as a valuable reference in this
exercise of cross calibrating GeMS on-sky wind estimates with model
predictions. In this contribution we achieved a two-fold results: (1) we
extended analysis on a much richer statistical sample (~ 43 nights), we
confirmed the preliminary results and we found an even better correlation
between GeMS observations and the atmospherical model with basically no cases
of not-negligible uncertainties; (2) we evaluate the possibility to use, as an
input for GeMS, the Meso-Nh estimates of the wind speed stratification in an
operational configuration. Under this configuration these estimates can be
provided many hours in advanced with respect to the observations and with a
very high temporal frequency (order of 2 minutes or less).Comment: 12 pages, 7 figures, Proc. SPIE 9909 "Adaptive Optics Systems V",
99093B, 201
Towards an automatic wind speed and direction profiler for Wide Field AO systems
Wide Field Adaptive Optics (WFAO) systems are among the most sophisticated AO
systems available today on large telescopes. The knowledge of the vertical
spatio-temporal distribution of the wind speed (WS) and direction (WD) are
fundamental to optimize the performance of such systems. Previous studies
already proved that the Gemini Multi-Conjugated AO system (GeMS) is able to
retrieve measurements of the WS and WD stratification using the SLODAR
technique and to store measurements in the telemetry data. In order to assess
the reliability of these estimates and of the SLODAR technique applied to such
a kind of complex AO systems, in this study we compared WS and WD retrieved
from GeMS with those obtained with the atmospherical model Meso-Nh on a rich
statistical sample of nights. It has been previously proved that, the latter
technique, provided an excellent agreement with a large sample of
radiosoundings both, in statistical terms and on individual flights. It can be
considered, therefore, as an independent reference. The excellent agreement
between GeMS measurements and the model that we find in this study, proves the
robustness of the SLODAR approach. To by-pass the complex procedures necessary
to achieve automatic measurements of the wind with GeMS, we propose a simple
automatic method to monitor nightly WS and WD using the Meso-Nh model
estimates. Such a method can be applied to whatever present or new generation
facilities supported by WFAO systems. The interest of this study is, therefore,
well beyond the optimization of GeMS performance.Comment: 9 figures, 2 tables, MNRAS accepte
Phase transformation B1 to B2 in TiC, TiN, ZrC and ZrN under pressure
Phase stability of various phases of MX (M = Ti, Zr; X = C, N) at equilibrium
and under pressure is examined based on first-principles calculations of the
electronic and phonon structures. The results reveal that all B1 (NaCl-type) MX
structures undergo a phase transition to the B2-structures under high pressure
in agreement with the previous total-energy calculations. The B1-MX structures
are dynamically stable under very high pressure (210-570 GPa). The
pressure-induced B2 (CsCl-type) MC phases are dynamically unstable even at high
pressures, and TiN and ZrN are found to crystallize with the B2-structure only
at pressures above 55 GPa. The first-order B1-to-B2 phase transition in these
nitrides is not related to the softening of phonon modes, and the dynamical
instability of B2-MX is associated with a high density of states at the Fermi
level.Comment: 9 pages, 4 figure
Fostering computational thinking skills with a tangible blocks programming environment
Computational Thinking has recently returned into the limelight as an essential skill to have for both the general public and disciplines outside Computer Science. It encapsulates those thinking skills integral to solving complex problems using a computer, thus widely applicable in our technological society. Several public initiatives such as the Hour of Code successfully introduced it to millions of people of different ages and backgrounds, mostly using Blocks Programming Environments like Scratch that lower the barriers of programming and facilitate learning. In this paper we present our arguments for fostering Computational Thinking skills using a Blocks Programming Environment augmented with a Tangible User Interface, namely by exploiting objects whose interactions with the physical environment are mapped to digital actions performed on the system. Our demonstration includes a working prototype implementing our Tangible Blocks Programming Environment called TAPAS
Characterizing dynamics with covariant Lyapunov vectors
A general method to determine covariant Lyapunov vectors in both discrete-
and continuous-time dynamical systems is introduced. This allows to address
fundamental questions such as the degree of hyperbolicity, which can be
quantified in terms of the transversality of these intrinsic vectors. For
spatially extended systems, the covariant Lyapunov vectors have localization
properties and spatial Fourier spectra qualitatively different from those
composing the orthonormalized basis obtained in the standard procedure used to
calculate the Lyapunov exponents.Comment: 4 pages, 3 figures, submitted to Physical Review letter
Evaluation of filtering techniques to increase the reliability of meteo forecasts for ground-based telescopes
In this contribution we evaluate the impact of filtering techniques in
enhancing the accuracy of forecasts of optical turbulence and atmospheric
parameters critical for ground-based telescopes. These techniques make use of
the data continuously provided by the telescope sensors and instruments to
improve the performances of real-time forecasts which have an impact on the
telescope operation. In previous works we have already shown how a mesoscale
high-frequency forecast (Meso-NH and Astro-Meso-Nh models) can produce reliable
predictions of different atmospheric parameters and the optical turbulence. The
mesoscale forecast has an advantage on the global model in having a better
implementation of the physical atmospheric processes, including turbulence, and
produces an output with greater spatial resolution (up to 100m or beyond).
Filtering techniques that make use of the real-time sensor data at the
telescope may help in removing potential biases and trends which have an impact
on short term mesoscale forecast and, as a consequence, may increase the
accuracy of the final output. Given the complexity and cost of present and
future top-class telescope installations, each improvement of forecasts of
future observing conditions will definitely help in better allocating observing
time, especially in queue-mode operation, and will definitely benefit the
scientific community in medium-long term.Comment: 10 pages, 5 figure
Reflecting on Algorithmic Bias with Design Fiction:the MiniCoDe Workshops
In an increasingly complex everyday life, algorithms-often learned from data, i.e., machine learning (ML)-are used to make or assist with operational decisions. However, developers and designers usually are not entirely aware of how to reflect on social justice while designing ML algorithms and applications. Algorithmic social justice-i.e., designing algorithms including fairness, transparency, and accountability-aims at helping expose, counterbalance, and remedy bias and exclusion in future ML-based decision-making applications. How might we entice people to engage in more reflective practices that examine the ethical consequences of ML algorithmic bias in society? We developed and tested a design-fiction-driven methodology to enable multidisciplinary teams to perform intense, workshop-like gatherings to let potential ethical issues emerge and mitigate bias through a series of guided steps. With this contribution, we present an original and innovative use of design fiction as a method to reduce algorithmic bias in co-design activities.</p
Tackling Prejudice and Discrimination Towards Families with Same-Sex Parents: An Exploratory Study in Italy
Though studies have shown that the sexual orientation of parents does not influence their parenting skills or the well-being of their children, prejudice against same-sex families is still very widespread. Research has not sufficiently explored the ways in which parents tackle this prejudice. Using qualitative methodologies, in particular textual analyses, this study has analysed the discourse used by same-sex families to handle the prejudices that they face. The results highlighted that conflicts, which may even be ideological in nature, are sometimes created between traditional families and “atypical” families. These often result in estrangement and isolation from their own family and the communities to which they belong, in turn damaging the growth of the children involved. Furthermore, means for moving beyond conflict, sharing experiences and effectively tackling prejudices are also discussed
High accuracy short-term PWV operational forecast at the VLT and perspectives for sky background forecast
In this paper we present the first results ever obtained by applying the
autoregressive (AR) technique to the precipitable water vapour (PWV). The study
is performed at the Very Large Telescope. The AR technique has been recently
proposed to provide forecasts of atmospheric and astroclimatic parameters at
short time scales (up to a few hours) by achieving much better performances
with respect to the 'standard forecasts' provided early afternoon for the
coming night. The AR method uses the real-time measurements of the parameter of
interest to improve the forecasts performed with atmospherical models. We used
here measurements provided by LHATPRO, a radiometer measuring continuously the
PWV at the VLT. When comparing the AR forecast at 1h to the standard forecast,
we observe a gain factor of 8 (i.e. 800 per cent) in terms of
forecast accuracy. In the PWV 1 mm range, which is extremely critical
for infrared astronomical applications, the RMSE of the predictions is of the
order of just a few hundredth of millimetres (0.04 mm). We proved therefore
that the AR technique provides an important benefit to VLT science operations
for all the instruments sensitive to the PWV. Besides, we show how such an
ability in predicting the PWV can be useful also to predict the sky background
in the infrared range (extremely appealing for METIS). We quantify such an
ability by applying this method to the NEAR project (New Earth in the Alpha Cen
region) supported by ESO and Breakthrough Initiatives
An ant-colony based approach for real-time implicit collaborative information seeking
This document is an Accepted Manuscript of the following article: Alessio Malizia, Kai A. Olsen, Tommaso Turchi, and Pierluigi Crescenzi, ‘An ant-colony based approach for real-time implicit collaborative information seeking’, Information Processing & Management, Vol. 53 (3): 608-623, May 2017. Under embargo until 31 July 2018. The final, definitive version of this paper is available online at doi: https://doi.org/10.1016/j.ipm.2016.12.005, published by Elsevier Ltd.We propose an approach based on Swarm Intelligence — more specifically on Ant Colony Optimization (ACO) — to improve search engines’ performance and reduce information overload by exploiting collective users’ behavior. We designed and developed three different algorithms that employ an ACO-inspired strategy to provide implicit collaborative-seeking features in real time to search engines. The three different algorithms — NaïveRank, RandomRank, and SessionRank — leverage on different principles of ACO in order to exploit users’ interactions and provide them with more relevant results. We designed an evaluation experiment employing two widely used standard datasets of query-click logs issued to two major Web search engines. The results demonstrated how each algorithm is suitable to be employed in ranking results of different types of queries depending on users’ intent.Peer reviewedFinal Accepted Versio
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