23 resultados para Automatic call detector
Resumo:
The Zero Degree Calorimeter (ZDC) of the ATLAS experiment at CERN is placed in the TAN of the LHC collider, covering the pseudorapidity region higher than 8.3. It is composed by 2 calorimeters, each one longitudinally segmented in 4 modules, located at 140 m from the IP exactly on the beam axis. The ZDC can detect neutral particles during pp collisions and it is a tool for diffractive physics. Here we present results on the forward photon energy distribution obtained using p-p collision data at sqrt{s} = 7 TeV. First the pi0 reconstruction will be used for the detector calibration with photons, then we will show results on the forward photon energy distribution in p-p collisions and the same distribution, but obtained using MC generators. Finally a comparison between data and MC will be shown.
Resumo:
In this thesis three measurements of top-antitop differential cross section at an energy in the center of mass of 7 TeV will be shown, as a function of the transverse momentum, the mass and the rapidity of the top-antitop system. The analysis has been carried over a data sample of about 5/fb recorded with the ATLAS detector. The events have been selected with a cut based approach in the "one lepton plus jets" channel, where the lepton can be either an electron or a muon. The most relevant backgrounds (multi-jet QCD and W+jets) have been extracted using data driven methods; the others (Z+ jets, diboson and single top) have been simulated with Monte Carlo techniques. The final, background-subtracted, distributions have been corrected, using unfolding methods, for the detector and selection effects. At the end, the results have been compared with the theoretical predictions. The measurements are dominated by the systematic uncertainties and show no relevant deviation from the Standard Model predictions.
Resumo:
Multidetector row computed tomography over the last decade is commonly used in veterinary medicine. This new technology has an increased spatial and temporal resolution, could evaluate wider scanning range in shorter scanning time, providing an advanced imaging modality. Computed tomography angiographic studies are commonly used in veterinary medicine in order to evaluate vascular structures of the abdomen and the thorax. Pulmonary pathology in feline patients is a very common condition and usually is further evaluating with computed tomography. Up to date few references of the normal computed tomographic aspects of the feline thorax are reported. In this study a computed tomographic pulmonary angiography (CTPA) protocol is reported in normal cats and is compared with the up to date anatomical references. A CTPA protocol using a 64 MDCT in our study achieved high resolution images of the pulmonary arteries, pulmonary veins and bronchial lumen till the level of minor segmental branches. Feline pulmonary bronchial parenchyma demonstrates an architecture of mixed type with a monopedial model observed in the most anatomical parts and the dichotomic aspect is seen at the accessory lobe. The arterial and venous architecture is similar to the bronchial. Statistical analysis demonstrates the linear correlation of tracheal diameter to the felines weight. Vascular variations were noticed. The pulmonary venous system enters into the left atrium through three ostia (left cranial ostia: consisted of the anastomosis of the cranial and caudal portion of the left cranial pulmonary vein; right ostia: consisted of the anastomosis of the right cranial and middle pulmonary vein; and the caudal ostia: consisted of the anastomosis of the right and left caudal pulmonary vein). In conclusion CTPA is applicable in feline patients and provides an excellent imaging of the pulmonary arterial, venous and bronchial system till the level of minor segmental branches.
Resumo:
The thesis work concerns X-ray spectrometry for both medical and space applications and is divided into two sections. The first section addresses an X-ray spectrometric system designed to study radiological beams and is devoted to the optimization of diagnostic procedures in medicine. A parametric semi-empirical model capable of efficiently reconstructing diagnostic X-ray spectra in 'middle power' computers was developed and tested. In addition, different silicon diode detectors were tested as real-time detectors in order to provide a real-time evaluation of the spectrum during diagnostic procedures. This project contributes to the field by presenting an improved simulation of a realistic X-ray beam emerging from a common X-ray tube with a complete and detailed spectrum that lends itself to further studies of added filtration, thus providing an optimized beam for different diagnostic applications in medicine. The second section describes the preliminary tests that have been carried out on the first version of an Application Specific Integrated Circuit (ASIC), integrated with large area position-sensitive Silicon Drift Detector (SDD) to be used on board future space missions. This technology has been developed for the ESA project: LOFT (Large Observatory for X-ray Timing), a new medium-class space mission that the European Space Agency has been assessing since February of 2011. The LOFT project was proposed as part of the Cosmic Vision Program (2015-2025).
Resumo:
In distributed systems like clouds or service oriented frameworks, applications are typically assembled by deploying and connecting a large number of heterogeneous software components, spanning from fine-grained packages to coarse-grained complex services. The complexity of such systems requires a rich set of techniques and tools to support the automation of their deployment process. By relying on a formal model of components, a technique is devised for computing the sequence of actions allowing the deployment of a desired configuration. An efficient algorithm, working in polynomial time, is described and proven to be sound and complete. Finally, a prototype tool implementing the proposed algorithm has been developed. Experimental results support the adoption of this novel approach in real life scenarios.
Resumo:
People tend to automatically mimic facial expressions of others. If clear evidence exists on the effect of non-verbal behavior (emotion faces) on automatic facial mimicry, little is known about the role of verbal behavior (emotion language) in triggering such effects. Whereas it is well-established that political affiliation modulates facial mimicry, no evidence exists on whether this modulation passes also through verbal means. This research addressed the role of verbal behavior in triggering automatic facial effects depending on whether verbal stimuli are attributed to leaders of different political parties. Study 1 investigated the role of interpersonal verbs, referring to positive and negative emotion expressions and encoding them at different levels of abstraction, in triggering corresponding facial muscle activation in a reader. Study 2 examined the role of verbs expressing positive and negative emotional behaviors of political leaders in modulating automatic facial effects depending on the matched or mismatched political affiliation of participants and politicians of left-and right-wing. Study 3 examined whether verbs expressing happiness displays of ingroup politicians induce a more sincere smile (Duchenne) pattern among readers of same political affiliation relative to happiness expressions of outgroup politicians. Results showed that verbs encoding facial actions at different levels of abstraction elicited differential facial muscle activity (Study 1). Furthermore, political affiliation significantly modulated facial activation triggered by emotion verbs as participants showed more congruent and enhanced facial activity towards ingroup politicians’ smiles and frowns compared to those of outgroup politicians (Study 2). Participants facially responded with a more sincere smile pattern towards verbs expressing smiles of ingroup compared to outgroup politicians (Study 3). Altogether, results showed that the role of political affiliation in modulating automatic facial effects passes also through verbal channels and is revealed at a fine-grained level by inducing quantitative and qualitative differences in automatic facial reactions of readers.
Resumo:
Dysfunction of Autonomic Nervous System (ANS) is a typical feature of chronic heart failure and other cardiovascular disease. As a simple non-invasive technology, heart rate variability (HRV) analysis provides reliable information on autonomic modulation of heart rate. The aim of this thesis was to research and develop automatic methods based on ANS assessment for evaluation of risk in cardiac patients. Several features selection and machine learning algorithms have been combined to achieve the goals. Automatic assessment of disease severity in Congestive Heart Failure (CHF) patients: a completely automatic method, based on long-term HRV was proposed in order to automatically assess the severity of CHF, achieving a sensitivity rate of 93% and a specificity rate of 64% in discriminating severe versus mild patients. Automatic identification of hypertensive patients at high risk of vascular events: a completely automatic system was proposed in order to identify hypertensive patients at higher risk to develop vascular events in the 12 months following the electrocardiographic recordings, achieving a sensitivity rate of 71% and a specificity rate of 86% in identifying high-risk subjects among hypertensive patients. Automatic identification of hypertensive patients with history of fall: it was explored whether an automatic identification of fallers among hypertensive patients based on HRV was feasible. The results obtained in this thesis could have implications both in clinical practice and in clinical research. The system has been designed and developed in order to be clinically feasible. Moreover, since 5-minute ECG recording is inexpensive, easy to assess, and non-invasive, future research will focus on the clinical applicability of the system as a screening tool in non-specialized ambulatories, in order to identify high-risk patients to be shortlisted for more complex investigations.
Resumo:
A method for automatic scaling of oblique ionograms has been introduced. This method also provides a rejection procedure for ionograms that are considered to lack sufficient information, depicting a very good success rate. Observing the Kp index of each autoscaled ionogram, can be noticed that the behavior of the autoscaling program does not depend on geomagnetic conditions. The comparison between the values of the MUF provided by the presented software and those obtained by an experienced operator indicate that the procedure developed for detecting the nose of oblique ionogram traces is sufficiently efficient and becomes much more efficient as the quality of the ionograms improves. These results demonstrate the program allows the real-time evaluation of MUF values associated with a particular radio link through an oblique radio sounding. The automatic recognition of a part of the trace allows determine for certain frequencies, the time taken by the radio wave to travel the path between the transmitter and receiver. The reconstruction of the ionogram traces, suggests the possibility of estimating the electron density between the transmitter and the receiver, from an oblique ionogram. The showed results have been obtained with a ray-tracing procedure based on the integration of the eikonal equation and using an analytical ionospheric model with free parameters. This indicates the possibility of applying an adaptive model and a ray-tracing algorithm to estimate the electron density in the ionosphere between the transmitter and the receiver An additional study has been conducted on a high quality ionospheric soundings data set and another algorithm has been designed for the conversion of an oblique ionogram into a vertical one, using Martyn's theorem. This allows a further analysis of oblique soundings, throw the use of the INGV Autoscala program for the automatic scaling of vertical ionograms.