1,493 research outputs found
Feedback Implosion Suppression Algorithm for Reliable Multicast Data Transmission over Geostationary Satellite Networks
Le politiche agricole strutturali
Gli interventi strutturali in agricoltura presentano una struttura complessa che deriva principalmente dalle molteplici interrelazioni che stanno alla base dello sviluppo del settore agricolo e delle economie rurali. Alla complessit\ue0 di impostazione deriva anche la complessit\ue0 del momento della valutazione che, a seconda degli aspetti che si intendono indagare o delle relazioni che occorre far emergere, pu\uf2 richiedere una particolare impostazione metodologica. Fornire alle amministrazioni sempre migliori strumenti per il processo di policy making mediante l\u2019approfondimento delle relazioni tra problemi-attori-risorse-azioni-prodotti-risultati-impatti appare quindi la premessa per rendere veramente produttivo il processo di apprendimento dalle esperienze acquisite, facendo emergere tutti gli elementi che consentono di rendere pi\uf9 efficace ed efficiente l\u2019uso delle risorse pubbliche
Integrated adaptive approach for reliable multicast transmission over geostationary satellite networks
Multiple retransmission passes, in order to ensure bit-perfect reliability in multicast transmission, results in lower resource utilization and higher session delay. Hence, an integrated adaptive transmission via the use of a cross-layer strategy is proposed in this paper in order to increase forward and return link resource utilization. Specifically, the integration of Channel State Information (CSI) collection policies in the uplink and Channel-Aware Scheduling (CAS) in the downlink is proposed in the face of fluctuating channel conditions observed by multicast terminals. The integration approach can be mathematically represented by suppression error due to the way CSI is collected and suppressed in the return link. Particularly, the suppression error occurs since only a subset of users update their CSI values at any CSI collection instant. In relation to the analytical representation of the suppression error, the performance parameters are then verified via simulation results. From the comparison, it was found that the simulation and analytical results approach agreement at large numbers of terminals. This observation suits the multicast transmission over satellite networks which expect large numbers of terminals over wide coverage
Refolding dynamics of stretched biopolymers upon force quench
Single molecule force spectroscopy methods can be used to generate folding
trajectories of biopolymers from arbitrary regions of the folding landscape. We
illustrate the complexity of the folding kinetics and generic aspects of the
collapse of RNA and proteins upon force quench, using simulations of an RNA
hairpin and theory based on the de Gennes model for homopolymer collapse. The
folding time, , depends asymmetrically on and
where () is the stretch (quench) force, and
is the transition mid-force of the RNA hairpin. In accord with
experiments, the relaxation kinetics of the molecular extension, , occurs
in three stages: a rapid initial decrease in the extension is followed by a
plateau, and finally an abrupt reduction in that occurs as the native
state is approached.
The duration of the plateau increases as decreases
(where is the time in which the force is reduced from to ).
Variations in the mechanisms of force quench relaxation as is altered
are reflected in the experimentally measurable time-dependent entropy, which is
computed directly from the folding trajectories. An analytical solution of the
de Gennes model under tension reproduces the multistage stage kinetics in
. The prediction that the initial stages of collapse should also be a
generic feature of polymers is validated by simulation of the kinetics of
toroid (globule) formation in semiflexible (flexible) homopolymers in poor
solvents upon quenching the force from a fully stretched state. Our findings
give a unified explanation for multiple disparate experimental observations of
protein folding.Comment: 31 pages 11 figure
Project PROMETHEUS: Design and Construction of a Radio Frequency Quadrupole at TAEK
The PROMETHEUS Project is ongoing for the design and development of a 4-vane
radio frequency quadrupole (RFQ) together with its H+ ion source, a low energy
beam transport (LEBT) line and diagnostics section. The main goal of the
project is to achieve the acceleration of the low energy ions up to 1.5 MeV by
an RFQ (352 MHz) shorter than 2 meter. A plasma ion source is being developed
to produce a 20 keV, 1 mA H+ beam. Simulation results for ion source,
transmission and beam dynamics are presented together with analytical studies
performed with newly developed RFQ design code DEMIRCI. Simulation results
shows that a beam transmission 99% could be achieved at 1.7 m downstream
reaching an energy of 1.5 MeV. As the first phase an Aluminum RFQ prototype,
the so-called cold model, will be built for low power RF characterization. In
this contribution the status of the project, design considerations, simulation
results, the various diagnostics techniques and RFQ manufacturing issues are
discussed.Comment: 4 pages, 8 figures, Proceedings of the 2nd International Beam
Instrumentation Conference 2013 (IBIC'13), 16-19 Sep 2013, WEPC02, p. 65
A fully automatic, interpretable and adaptive machine learning approach to map burned area from remote sensing
The paper proposes a fully automatic algorithm approach to map burned areas from remote sensing characterized by human interpretable mapping criteria and explainable results. This approach is partially knowledge-driven and partially data-driven. It exploits active fire points to train the fusion function of factors deemed influential in determining the evidence of burned conditions from reflectance values of multispectral Sentinel-2 (S2) data. The fusion function is used to compute a map of seeds (burned pixels) that are adaptively expanded by applying a Region Growing (RG) algorithm to generate the final burned area map. The fusion function is an Ordered Weighted Averaging (OWA) operator, learnt through the application of a machine learning (ML) algorithm from a set of highly reliable fire points. Its semantics are characterized by two measures, the degrees of pessimism/optimism and democracy/monarchy. The former allows the prediction of the results of the fusion as affected by more false positives (commission errors) than false negatives (omission errors) in the case of pessimism, or vice versa; the latter foresees if there are only a few highly influential factors or many low influential ones that determine the result. The prediction on the degree of pessimism/optimism allows the expansion of the seeds to be appropriately tuned by selecting the most suited growing layer for the RG algorithm thus adapting the algorithm to the context. The paper illustrates the application of the automatic method in four study areas in southern Europe to map burned areas for the 2017 fire season. Thematic accuracy at each site was assessed by comparison to reference perimeters to prove the adaptability of the approach to the context; estimated average accuracy metrics are omission error = 0.057, commission error = 0.068, Dice coefficient = 0.94 and relative bias = 0.0046
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