Search results for "network"
showing 10 items of 7718 documents
"Table 28" of "Search for heavy charged long-lived particles in the ATLAS detector in 31.6 fb$^{-1}$ of proton-proton collision data at $\sqrt{s} = 1…
2019
Resolution and average of reconstructed ToF mass for a given simulated mass for ID+calo candidates.
"Table 24" of "Search for heavy charged long-lived particles in the ATLAS detector in 31.6 fb$^{-1}$ of proton-proton collision data at $\sqrt{s} = 1…
2019
Candidate reconstruction efficiency for ID+Calo selection (IDCaloEff).
Vallan verkostoissa : Per Brahe ja hänen klienttinsä 1600-luvun Ruotsin valtakunnassa
2011
Interpretability of Recurrent Neural Networks in Remote Sensing
2020
In this work we propose the use of Long Short-Term Memory (LSTM) Recurrent Neural Networks for multivariate time series of satellite data for crop yield estimation. Recurrent nets allow exploiting the temporal dimension efficiently, but interpretability is hampered by the typically overparameterized models. The focus of the study is to understand LSTM models by looking at the hidden units distribution, the impact of increasing network complexity, and the relative importance of the input covariates. We extracted time series of three variables describing the soil-vegetation status in agroe-cosystems -soil moisture, VOD and EVI- from optical and microwave satellites, as well as available in si…
FMapper: Scalable read mapper based on succinct hash index on SunWay TaihuLight
2022
Abstract One of the most important application in bioinformatics is read mapping. With the rapidly increasing number of reads produced by next-generation sequencing (NGS) technology, there is a need for fast and efficient high-throughput read mappers. In this paper, we present FMapper – a highly scalable read mapper on the TaihuLight supercomputer optimized for its fourth-generation ShenWei many-core architecture (SW26010). In order to fully exploit the computational power of the SW26010, we employ dynamic scheduling of tasks, asynchronous I/O and data transfers and implement a vectorized version of the banded Myers algorithm tailored to the 256 bit vector registers of the SW26010. Our perf…
Spiking Neural Networks models targeted for implementation on Reconfigurable Hardware
2017
La tesis presentada se centra en la denominada tercera generación de redes neuronales artificiales, las Redes Neuronales Spiking (SNN) también llamadas ‘de espigas’ o ‘de eventos’. Este campo de investigación se convirtió en un tema popular e importante en la última década debido al progreso de la neurociencia computacional. Las Redes Neuronales Spiking, que tienen no sólo la plasticidad espacial sino también temporal, ofrecen una alternativa prometedora a las redes neuronales artificiales clásicas (ANN) y están más cerca de la operación real de las neuronas biológicas ya que la información se codifica y transmite usando múltiples espigas o eventos en forma de trenes de pulsos. Este campo h…
Nanomechanics of individual aerographite tetrapods
2017
Carbon-based three-dimensional aerographite networks, built from interconnected hollow tubular tetrapods of multilayer graphene, are ultra-lightweight materials recently discovered and ideal for advanced multifunctional applications. In order to predict the bulk mechanical behaviour of networks it is very important to understand the mechanics of their individual building blocks. Here we characterize the mechanical response of single aerographite tetrapods via in situ scanning electron and atomic force microscopy measurements. To understand the acquired results, which show that the overall behaviour of the tetrapod is governed by the buckling of the central joint, a mechanical nonlinear mode…
Processing of 3D Models for Networking of CH in Geomatics
2020
In recent times the possibility of reconstruction of complex 3D Cultural Heritage (CH) environments has opened new scenarios for touristic and scientific aims. The different needs for networking or conservation purposes of CH lead to study proper structuring of 3D models. In light of this, a scientific approach has been developed in order to test the networking capabilities, comparing different loading configurations of 3D environments with multiple combinations of 3D models inside them, considering different solutions. This experimentation has been based on WebGL-HTML5 technologies and allowed to discover the true balance between performances of proposed system, the quality of visualizatio…
A neural architecture for 3D segmentation
2003
An original neural scheme for segmentation of range data is presented, which is part of a more general 3D vision system for robotic applications. The entire process relies on a neural architecture aimed to perform first order image irradiance analysis, that is local estimation of magnitude and orientation of the image irradiance gradient.In the case of dense 3D data, irradiance is replaced by depth information so irradiance analysis of these pseudo-images provides knowledge about the actual curvature of the acquired surfaces. In particular, boundaries and contours due to mutual occlusions can be detected very well while there are no false contours due to rapid changing in brightness or colo…
A Geometrical Channel Model for MIMO Mobile-to-Mobile Fading Channels in Cooperative Networks
2009
This paper deals with the modeling and analysis of narrowband multiple-input multiple-output (MIMO) mobile- to-mobile (M2M) fading channels in relay-based cooperative networks. Non-line-of-sight (NLOS) propagation conditions are assumed in the transmission links from the source mobile station to the destination mobile station via the mobile relay. A stochastic narrowband MIMO M2M reference channel model is derived from the geometrical three-ring scattering model, where it is assumed that an infinite number of local scatterers surround the source mobile station, the mobile relay, and the destination mobile station. The complex channel gains associated with the new reference channel model are…