8 documents found, page 1 of 1

Muon tomography with Resistive Plate Chambers for geological characterization

Muon tomography is one of several fields of applied physics that have witnessed the successful use of particle detection based on Resistive Plate Chambers (RPC). In this work, we report on an innovative project concerning transmission muography for geological characterization. For this purpose, a muon telescope built of four RPC planes was mounted on an adjustable structure and the telescope's response to atmos...

Avanços no projeto LouMu – Muografia para levantamentos geofísicos

O Projeto LouMu é uma colaboração em curso entre o Laboratório de Instrumentação e Física Experimental de Partículas, o Instituto de Ciências da Terra – Universidade de Évora e o Centro Ciência Viva do Lousal, contando ainda com o apoio do Laboratório Nacional de Energia e Geologia. O objetivo é explorar o potencial da técnica de muografia na Mina do Lousal, com a finalidade de criar as condições para a utiliza...

Muon tomography with Resistive Plate Chambers for geological characterization

ABSTRACT: Muon tomography is one of several fields of applied physics that have witnessed the successful use of particle detection based on Resistive Plate Chambers (RPC). In this work, we report on an innovative project concerning transmission muography for geological characterization. For this purpose, a muon telescope built of four RPC planes was mounted on an adjustable structure and the telescope's respons...

Muography in the University and in the Museum

Learning to classify seismic images with deep optimum-path forest

Made available in DSpace on 2022-04-29T22:42:10Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-01-10; Due to the lack of labeled information, clustering techniques have been paramount in the last years once more. In this paper, inspired by the deep learning phenomenon, we presented a multi-scale approach to obtain more refined cluster representations of the Optimum-Path Forest (OPF) classifier, which ha...

BreastNet: Breast cancer categorization using convolutional neural networks

Made available in DSpace on 2021-06-25T10:11:11Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-07-01; Breast cancer is usually classified as either benign or malignant, where the former is not considered hazardous to health. Nonetheless, the benign tumors must be periodically monitored to control their activity and to prevent them from becoming malignant eventually. Several automated techniques have bee...

Learning to Classify Seismic Images with Deep Optimum-Path Forest

Made available in DSpace on 2018-11-26T17:39:43Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-01-01; Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP); Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq); Due to the lack of labeled information, clustering techniques have been paramount in the last years once more. In this paper, inspired by the deep learning phenomenon, we ...

Multilayer Perceptron Neural Networks Training Through Charged System Search an...

The non-technical loss is not a problem with trivial solution or regional character and its minimization represents the guarantee of investments in product quality and maintenance of power systems, introduced by a competitive environment after the period of privatization in the national scene. In this paper, we show how to improve the training phase of a neural network-based classifier using a recently proposed...