Search results for "methodologies"
showing 10 items of 2106 documents
Luminosity determination in pp collisions at s=7 TeV using the ATLAS detector at the LHC
2011
Measurements of luminosity obtained using the ATLAS detector during early running of the Large Hadron Collider (LHC) at s√=7 TeV are presented. The luminosity is independently determined using several detectors and multiple algorithms, each having different acceptances, systematic uncertainties and sensitivity to background. The ratios of the luminosities obtained from these methods are monitored as a function of time and of μ, the average number of inelastic interactions per bunch crossing. Residual time- and μ-dependence between the methods is less than 2% for 0<μ<2.5. Absolute luminosity calibrations, performed using beam separation scans, have a common systematic uncertainty of ±11%, do…
Limits on the production of the standard model Higgs boson in pp collisions at root s=7 TeV with the ATLAS detector
2011
A search for the Standard Model Higgs boson at the Large Hadron Collider (LHC) running at a centre-of-mass energy of 7 TeV is reported, based on a total integrated luminosity of up to 40 pb−1 collected by the ATLAS detector in 2010. Several Higgs boson decay channels: H→γγ, H→ZZ(∗)→ℓℓℓℓ, H→ZZ→ℓℓνν, H→ZZ→ℓℓqq, H→WW(∗)→ℓνℓν and H→WW→ℓνqq (ℓ is e, μ) are combined in a mass range from 110 GeV to 600 GeV. The highest sensitivity is achieved in the mass range between 160 GeV and 170 GeV, where the expected 95% CL exclusion sensitivity is at Higgs boson production cross sections 2.3 times the Standard Model prediction. Upper limits on the cross section for its production are determined. Models wit…
A naive approach to compose aerial images in a mosaic fashion
2002
There is growing interest in multiple sequence image analysis to represent those data in a new landscape, for instance reconstruction of old films, mosaicing of images. This paper focuses attention on the mosaic problem; it introduces a naive method to link together images where a common part of the scene is present among two images. An application has been developed to test the method on aerial sequences of images. Given the long distance of aircraft from the scene, the method assumes images without distortions and without problems of prospective. Moreover, the application does not need any additional parameters coming from human experience and for this reason it can be thought of as a ful…
Anisotropy and chemical composition of ultra-high energy cosmic rays using arrival directions measured by the Pierre Auger Observatory
2011
The Pierre Auger Collaboration has reported evidence for anisotropy in the distribution of arrival directions of the cosmic rays with energies $E>E_{th}=5.5\times 10^{19}$ eV. These show a correlation with the distribution of nearby extragalactic objects, including an apparent excess around the direction of Centaurus A. If the particles responsible for these excesses at $E>E_{th}$ are heavy nuclei with charge $Z$, the proton component of the sources should lead to excesses in the same regions at energies $E/Z$. We here report the lack of anisotropies in these directions at energies above $E_{th}/Z$ (for illustrative values of $Z=6,\ 13,\ 26$). If the anisotropies above $E_{th}$ are du…
Binding mode analysis of ABCA7 for the prediction of novel Alzheimer's disease therapeutics
2021
Graphical abstract
Air-Coupled Imaging Method Applied to the Study and Conservation of Paintings
2007
An air-coupled acoustical imaging method for the study of wooden panel paintings is presented. After a brief overview of the state of the art, an introduction is given regarding the production technique of the art object under investigation. The technology employed is described in detail, as well as the proposed method. After a feasibility campaign of experiments, real ancient paintings have been investigated by means of a through-transmission and a single-sided lay-out. Defects were imaged in all the objects examined and in both the configurations adopted
Archetypal analysis: an alternative to clustering for unsupervised texture segmentation
2019
Texture segmentation is one of the main tasks in image applications, specifically in remote sensing, where the objective is to segment high-resolution images of natural landscapes into different cover types. Often the focus is on the selection of discriminant textural features, and although these are really fundamental, there is another part of the process that is also influential, partitioning different homogeneous textures into groups. A methodology based on archetype analysis (AA) of the local textural measurements is proposed. AA seeks the purest textures in the image and it can find the borders between pure textures, as those regions composed of mixtures of several archetypes. The prop…
An ASSOM neural network to represent actions performed by an autonomous agent
1997
An ASSOM neural network to describe the action performed by an autonomous reactive agent is proposed. The neural network receives in input the sequences of data acquired by the agent internal sensors and it classifies them by generating the corresponding symbolic assertions. Experimental results performed on a RWI B12 autonomous robot are reported.
Automatic Segmentation of HEp-2 Cells Based on Active Contours Model
2018
In the past years, a great deal of effort was put into research regarding Indirect Immunofluorescence techniques with the aim of development of CAD systems. In this work a method for segmenting HEp-2 cells in IIF images is presented. Such task is one of the most challenging of automated IIF analysis, because the segmentation algorithm has to cope with a large heterogeneity of shapes and textures. In order to address this problem, numerous techniques and their combinations were evaluated, in a process aimed at maximizing the figure of merit. The proposed method, for a greater definition of cellular contours, uses the active contours in the last phase of the process. The initial conditions, c…
Unsupervised low-key image segmentation using curve evolution approach
2013
Low-key images widely exist in imaging-based systems such as space telescopes, medical imaging equipment, machine vision systems. Unsupervised low-key image segmentation is an important process for image analysis or digital measurement in these applications. In this paper, a novel active contour model with the probability density function (PDF) of gamma distribution for image segmentation is proposed. The flexible gamma distribution is used to describe both of the heterogeneous foreground and dark background in a low-key image. Besides, an unsupervised curve initialization method is also designed in this paper, which helps to accelerate the convergence speed of curve evolution. The effectiv…