Search results for "DETECT"
showing 10 items of 5902 documents
Deep-learning based reconstruction of the shower maximum X max using the water-Cherenkov detectors of the Pierre Auger Observatory
2021
The atmospheric depth of the air shower maximum $X_{\mathrm{max}}$ is an observable commonly used for the determination of the nuclear mass composition of ultra-high energy cosmic rays. Direct measurements of $X_{\mathrm{max}}$ are performed using observations of the longitudinal shower development with fluorescence telescopes. At the same time, several methods have been proposed for an indirect estimation of $X_{\mathrm{max}}$ from the characteristics of the shower particles registered with surface detector arrays. In this paper, we present a deep neural network (DNN) for the estimation of $X_{\mathrm{max}}$. The reconstruction relies on the signals induced by shower particles in the groun…
Responsivity measurements of SiC photodiodes
2014
We investigated the technical features of three novel classes of 4H-SiC vertical Schottky UV photodiodes (henceforth, named SiC8, SiC10, SiC20) employing Ni2Si interdigitated strips whose pitch size is 8, 10 and 20 µm respectively [1] and based on the pinch-off surface effect.
Development of high resolution and efficiency detectors based on Silicon Photomultipliers (SIPMS) and continuous crystals for medical physics applica…
2017
El trabajo presentado en esta tesis introduce y evalúa dos aspectos novedosos en los detectores de rayos gamma para imagen médica: el uso de fotomultiplicadores de silicio (SiPMs, en inglés) acoplados a cristales centelleadores continuos. Tradicionalmente, los tubos fotomultiplicadores (PMTs, en inglés) acoplados a cristales centelleadores han jugado un papel dominante en la detección de rayos gamma. En los últimos años ha aparecido un nuevo tipo de fotodetector de estado sólido, el SiPM, como opción para sustituir a los PMTs en ciertas aplicaciones. Los SiPMs tienen una ganancia y una eficiencia cuántica altas, un voltaje de operación bajo y unas propiedades temporales excelentes. Además, …
Advanced performance monitoring for self-healing cellular mobile networks
2015
This dissertation is devoted to development and validation of advanced per- formance monitoring system for existing and future cellular mobile networks. Knowledge mining techniques are employed for analysis of user specific logs, collected with Minimization of Drive Tests (MDT) functionality. Ever increas- ing quality requirements, expansion of the mobile networks and their extend- ing heterogeneity, call for effective automatic means of performance monitoring. Nowadays, network operation is mostly controlled manually through aggregated key performance indicators and statistical profiles. These methods are are not able to fully address the dynamism and complexity of modern mobile networks. Se…
Video Scene analysis for a configurable hardware accelerator dedicated to Smart Camera
2012
International audience; According to the Center for Research and Prevention of Injuries report, fall-caused injuries of elderly people in UE- 27 are five times as frequent as other injury causes which reduce considerably their mobility and independence. Among the diverse applications of computer vision systems, object detection and event recognition are of the most prominent related recognition and motion analysis, that is, researchers had the idea to spread it in fall detection. The fall event, extracted automatically from the video scene represents itself, crucial information that can be used to alert emergency. In this context, visual information on the corresponding scene is highly impo…
An Intrusion Detection System for Fog Computing and IoT based Logistic Systems using a Smart Data Approach
2016
The Internet of Things (IoT) is widely used in advanced logistic systems. Safety and security of such systems are utmost important to guarantee the quality of their services. However, such systems are vulnerable to cyber-attacks. Development of lightweight anomaly based intrusion detection systems (IDS) is one of the key measures to tackle this problem. In this paper, we present a new distributed and lightweight IDS based on an Artificial Immune System (AIS). The IDS is distributed in a three-layered IoT structure including the cloud, fog and edge layers. In the cloud layer, the IDS clusters primary network traffic and trains its detectors. In the fog layer, we take advantage of a smart dat…
Ti Alloyed α-Ga2O3: Route towards Wide Band Gap Engineering
2020
The suitability of Ti as a band gap modifier for &alpha
Models and methods for space and space-time interactions in complex point processes with applications on earthquakes
Bayesian temporal and spatio-temporal Markov switching models for the detection of influenza outbreaks
2017
Influenza is a disease which affects millions of people every year and causes hundreds of thousends of deads every year. This disease causes substantial direct and indirect costs every year. The influenza epidemic have a particular behavior which shapes the statistical methods for their detection. Seasonal epidemics happen virtually every year in the temperate parts of the globe during the cold months and extend throughout whole regions, countries and even continents. Besides the seasonal epidemics, some nonseasonal epidemics can be observed at unexpected times, usually caused by strains which jump the barrier between animals and humans, as happened with the well known Swine Flu epidemic, w…
Intelligent solutions for real-life data-driven applications
2017
The subject of this thesis belongs to the topic of machine learning or, specifically, to the development of advanced methods for regression analysis, clustering, and anomaly detection. Industry is constantly seeking improved production practices and minimized production time and costs. In connection to this, several industrial case studies are presented in which mathematical models for predicting paper quality were proposed. The most important variables for the prediction models are selected based on information-theoretic measures and regression trees approach. The rest of the original papers are devoted to unsupervised machine learning. The main focus is developing advanced spectral cluster…