235,491 research outputs found
Adaptive data synchronization algorithm for IoT-oriented low-power wide-area networks
The Internet of Things (IoT) is by now very close to be realized, leading the world towards a new technological era where people’s lives and habits will be definitively revolutionized. Furthermore, the incoming 5G technology promises significant enhancements concerning the Quality of Service (QoS) in mobile communications. Having billions of devices simultaneously connected has opened new challenges about network management and data exchange rules that need to be tailored to the characteristics of the considered scenario. A large part of the IoT market is pointing to Low-Power Wide-Area Networks (LPWANs) representing the infrastructure for several applications having energy saving as a mandatory goal besides other aspects of QoS. In this context, we propose a low-power IoT-oriented file synchronization protocol that, by dynamically optimizing the amount of data to be transferred, limits the device level of interaction within the network, therefore extending the battery life. This protocol can be adopted with different Layer 2 technologies and provides energy savings at the IoT device level that can be exploited by different applications
Quantum ESPRESSO: a modular and open-source software project for quantum simulations of materials
Quantum ESPRESSO is an integrated suite of computer codes for
electronic-structure calculations and materials modeling, based on
density-functional theory, plane waves, and pseudopotentials (norm-conserving,
ultrasoft, and projector-augmented wave). Quantum ESPRESSO stands for "opEn
Source Package for Research in Electronic Structure, Simulation, and
Optimization". It is freely available to researchers around the world under the
terms of the GNU General Public License. Quantum ESPRESSO builds upon
newly-restructured electronic-structure codes that have been developed and
tested by some of the original authors of novel electronic-structure algorithms
and applied in the last twenty years by some of the leading materials modeling
groups worldwide. Innovation and efficiency are still its main focus, with
special attention paid to massively-parallel architectures, and a great effort
being devoted to user friendliness. Quantum ESPRESSO is evolving towards a
distribution of independent and inter-operable codes in the spirit of an
open-source project, where researchers active in the field of
electronic-structure calculations are encouraged to participate in the project
by contributing their own codes or by implementing their own ideas into
existing codes.Comment: 36 pages, 5 figures, resubmitted to J.Phys.: Condens. Matte
Variational Hamiltonian Monte Carlo via Score Matching
Traditionally, the field of computational Bayesian statistics has been
divided into two main subfields: variational methods and Markov chain Monte
Carlo (MCMC). In recent years, however, several methods have been proposed
based on combining variational Bayesian inference and MCMC simulation in order
to improve their overall accuracy and computational efficiency. This marriage
of fast evaluation and flexible approximation provides a promising means of
designing scalable Bayesian inference methods. In this paper, we explore the
possibility of incorporating variational approximation into a state-of-the-art
MCMC method, Hamiltonian Monte Carlo (HMC), to reduce the required gradient
computation in the simulation of Hamiltonian flow, which is the bottleneck for
many applications of HMC in big data problems. To this end, we use a {\it
free-form} approximation induced by a fast and flexible surrogate function
based on single-hidden layer feedforward neural networks. The surrogate
provides sufficiently accurate approximation while allowing for fast
exploration of parameter space, resulting in an efficient approximate inference
algorithm. We demonstrate the advantages of our method on both synthetic and
real data problems
Internal report cluster 1: Urban freight innovations and solutions for sustainable deliveries (3/4)
Technical report about sustainable urban freight solutions, part 3 of
- …