Microwave Discharge Ion Sources

This chapter describes the basic principles, design features and characteristics of microwave discharge ion sources. A suitable source for the production of intense beams for high-power accelerators must satisfy the requirements of high brightness, stability and reliability. The 2.45 GHz off-resonance microwave discharge sources are ideal devices to generate the required beams, as they produce multimilliampere beams of protons, deuterons and singly charged ions. A description of different technical designs will be given, analysing their performance, with particular attention being paid to the quality of the beam, especially in terms of its emittance.Comment: 21 pages, contribution to the CAS-CERN Accelerator School: Ion Sources, Senec, Slovakia, 29 May - 8 June 2012, edited by R. Baile

Benchmark Analysis of Representative Deep Neural Network Architectures

This work presents an in-depth analysis of the majority of the deep neural networks (DNNs) proposed in the state of the art for image recognition. For each DNN multiple performance indices are observed, such as recognition accuracy, model complexity, computational complexity, memory usage, and inference time. The behavior of such performance indices and some combinations of them are analyzed and discussed. To measure the indices we experiment the use of DNNs on two different computer architectures, a workstation equipped with a NVIDIA Titan X Pascal and an embedded system based on a NVIDIA Jetson TX1 board. This experimentation allows a direct comparison between DNNs running on machines with very different computational capacity. This study is useful for researchers to have a complete view of what solutions have been explored so far and in which research directions are worth exploring in the future; and for practitioners to select the DNN architecture(s) that better fit the resource constraints of practical deployments and applications. To complete this work, all the DNNs, as well as the software used for the analysis, are available online.Comment: Will appear in IEEE Acces

Conductor losses calculation in two-dimensional simulations of H-plane rectangular waveguides

This paper presents a novel numerical approach to simulate H-plane rectangular-waveguide microwave circuits considering a reduced quasi-2D simulation domain with benefits for computational cost and time. With the aim to evaluate the attenuation of the full height 3D component, we propose a modified expression for the waveguide top/bottom wall conductivity. Numerical 2D simulations are validated against results from full wave 3-D commercial electromagnetic simulator. After a benchmark on a simple straight waveguide model, the method has been successfully applied to an asymmetric un-balanced power splitter, where an accurate power loss prediction is mandatory. Simulation time and memory consumption can be reduced by a factor ten and seven respectively, in comparison with complete 3D geometries. Finally, we show that, also for quasi-2D E-bend waveguide, a case where the translational H-plane symmetry is broken, the error on conductor losses computation is mitigated by our approach since the method remains still valid in a first approximation

Aesthetics Assessment of Images Containing Faces

Recent research has widely explored the problem of aesthetics assessment of images with generic content. However, few approaches have been specifically designed to predict the aesthetic quality of images containing human faces, which make up a massive portion of photos in the web. This paper introduces a method for aesthetic quality assessment of images with faces. We exploit three different Convolutional Neural Networks to encode information regarding perceptual quality, global image aesthetics, and facial attributes; then, a model is trained to combine these features to explicitly predict the aesthetics of images containing faces. Experimental results show that our approach outperforms existing methods for both binary, i.e. low/high, and continuous aesthetic score prediction on four different databases in the state-of-the-art.Comment: Accepted by ICIP 201

Disentangling Image Distortions in Deep Feature Space

Previous literature suggests that perceptual similarity is an emergent property shared across deep visual representations. Experiments conducted on a dataset of human-judged image distortions have proven that deep features outperform classic perceptual metrics. In this work we take a further step in the direction of a broader understanding of such property by analyzing the capability of deep visual representations to intrinsically characterize different types of image distortions. To this end, we firstly generate a number of synthetically distorted images and then we analyze the features extracted by different layers of different Deep Neural Networks. We observe that a dimension-reduced representation of the features extracted from a given layer permits to efficiently separate types of distortions in the feature space. Moreover, each network layer exhibits a different ability to separate between different types of distortions, and this ability varies according to the network architecture. Finally, we evaluate the exploitation of features taken from the layer that better separates image distortions for: i) reduced-reference image quality assessment, and ii) distortion types and severity levels characterization on both single and multiple distortion databases. Results achieved on both tasks suggest that deep visual representations can be unsupervisedly employed to efficiently characterize various image distortions

Políticas de Inserção e permanência universitária para população indígena

Relatório Final referente ao Edital IMEA 06/2018 " Estudos sobre a UNILA"IMEA-UNIL

Study of charge state enhancement by means of the coupling of a Laser Ion Source to the ECR ion source SERSE

The possibility to produce intense ion beams from solid elements, by using a pulsed Laser ion source as the first stage of the superconducting ECR ion source SERSE is discussed in the following. The Laser ion source may be used to produce negative or positive ions and electrons that are injected into the plasma of SERSE. The design of the experimental setup and the study of the extraction of ions from a target by means of Nd:Yag laser irradiation are briefly described. This Laser ion source will be located in the plasma chamber of the source SERSE, in presence of its magnetic field. A simple evaluation of the charge state enhancement inside the ECR plasma is also presented in the following