Search results for "LAB"
showing 10 items of 7932 documents
Combination of the top-quark mass measurements from the Tevatron collider
2012
Aaltonen, T. et al.
Combination of CDF and D0 measurements of the W boson helicity in top quark decays
2012
Aaltonen, T. et al.
Higgs boson studies at the Tevatron
2013
We combine searches by the CDF and D0 Collaborations for the standard model Higgs boson with mass in the range 90-200 GeV/c2 produced in the gluon-gluon fusion, WH, ZH, tt̄H, and vector boson fusion processes, and decaying in the H→bb̄, H→W+W-, H→ZZ, H→τ+τ-, and H→γγ modes. The data correspond to integrated luminosities of up to 10 fb-1 and were collected at the Fermilab Tevatron in pp̄ collisions at √s=1.96 TeV. The searches are also interpreted in the context of fermiophobic and fourth generation models. We observe a significant excess of events in the mass range between 115 and 140 GeV/c2. The local significance corresponds to 3.0 standard deviations at mH=125 GeV/c2, consistent with the…
Evidence for a Particle Produced in Association with Weak Bosons and Decaying to a Bottom-Antibottom Quark Pair in Higgs Boson Searches at the Tevatr…
2012
Aaltonen, T. et al.
Measurement of the cosmic ray energy spectrum using hybrid events of the Pierre Auger Observatory
2012
The energy spectrum of ultra-high energy cosmic rays above 10$^{18}$ eV is measured using the hybrid events collected by the Pierre Auger Observatory between November 2005 and September 2010. The large exposure of the Observatory allows the measurement of the main features of the energy spectrum with high statistics. Full Monte Carlo simulations of the extensive air showers (based on the CORSIKA code) and of the hybrid detector response are adopted here as an independent cross check of the standard analysis (Phys. Lett. B 685, 239 (2010)). The dependence on mass composition and other systematic uncertainties are discussed in detail and, in the full Monte Carlo approach, a region of confiden…
Inducing the Lyndon Array
2019
In this paper we propose a variant of the induced suffix sorting algorithm by Nong (TOIS, 2013) that computes simultaneously the Lyndon array and the suffix array of a text in $O(n)$ time using $\sigma + O(1)$ words of working space, where $n$ is the length of the text and $\sigma$ is the alphabet size. Our result improves the previous best space requirement for linear time computation of the Lyndon array. In fact, all the known linear algorithms for Lyndon array computation use suffix sorting as a preprocessing step and use $O(n)$ words of working space in addition to the Lyndon array and suffix array. Experimental results with real and synthetic datasets show that our algorithm is not onl…
SIFT Matching by Context Exposed
2023
This paper investigates how to step up local image descriptor matching by exploiting matching context information. Two main contexts are identified, originated respectively from the descriptor space and from the keypoint space. The former is generally used to design the actual matching strategy while the latter to filter matches according to the local spatial consistency. On this basis, a new matching strategy and a novel local spatial filter, named respectively blob matching and Delaunay Triangulation Matching (DTM) are devised. Blob matching provides a general matching framework by merging together several strategies, including rank-based pre-filtering as well as many-to-many and symmetri…
FIRST
2018
Thanks to the collective action of participating smartphone users, mobile crowdsensing allows data collection at a scale and pace that was once impossible. The biggest challenge to overcome in mobile crowdsensing is that participants may exhibit malicious or unreliable behavior, thus compromising the accuracy of the data collection process. Therefore, it becomes imperative to design algorithms to accurately classify between reliable and unreliable sensing reports. To address this crucial issue, we propose a novel Framework for optimizing Information Reliability in Smartphone-based participaTory sensing (FIRST) that leverages mobile trusted participants (MTPs) to securely assess the reliabil…
Using Hankel matrices for dynamics-based facial emotion recognition and pain detection
2015
This paper proposes a new approach to model the temporal dynamics of a sequence of facial expressions. To this purpose, a sequence of Face Image Descriptors (FID) is regarded as the output of a Linear Time Invariant (LTI) system. The temporal dynamics of such sequence of descriptors are represented by means of a Hankel matrix. The paper presents different strategies to compute dynamics-based representation of a sequence of FID, and reports classification accuracy values of the proposed representations within different standard classification frameworks. The representations have been validated in two very challenging application domains: emotion recognition and pain detection. Experiments on…
A Deep Network Approach to Multitemporal Cloud Detection
2018
We present a deep learning model with temporal memory to detect clouds in image time series acquired by the Seviri imager mounted on the Meteosat Second Generation (MSG) satellite. The model provides pixel-level cloud maps with related confidence and propagates information in time via a recurrent neural network structure. With a single model, we are able to outline clouds along all year and during day and night with high accuracy.